{smcl}
{txt}{sf}{ul off}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\david\Dropbox\Spanish_Lottery\StataDos_RScripts\202406 Analysis\Ours_replication_pkg\NEW AND FINAL REPPKG\Logs\MainPaper_ElectoralEvidence_byelection_Tables.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}31 Oct 2025, 18:38:05
{txt}
{com}. 
. /*-----------------------------------------------------------------------------*
> * REPLICATION for "Do Provinces that Win the Spanish Christmas Lottery 
> Experience a Surge in  Incumbent Popularity? An Out-of-Sample Replication of 
> Bagues and Esteve-Volart (2016)". JPE Micro
> * Authors: Carolina Bernal, Donald Green, and David Vilalta
> 
> * What for: Code for Provincial Vote Shares for the Incumbent Party -- Tables A8
>  to A13 in the Appendix
> * Do file's author: David Vilalta
> **----------------------------------------------------------------------------*/
. 
. cls
{txt}
{com}. 
. global folder "C:/Users/david/Dropbox/Spanish_Lottery/StataDos_RScripts/202406 Analysis/Ours_replication_pkg/NEW AND FINAL REPPKG"
{txt}
{com}. 
. cd "${c -(}folder{c )-}"
{res}C:\Users\david\Dropbox\Spanish_Lottery\StataDos_RScripts\202406 Analysis\Ours_replication_pkg\NEW AND FINAL REPPKG
{txt}
{com}. 
. use "Data/Our_data/20250531_SpanishLottery_Complete_province.dta", clear 
{txt}
{com}. 
. * Path to figures and tables folders: 
. global tables "Results/Tables_Electoral/"
{txt}
{com}. global figures "Results/Figures_Electoral/" 
{txt}
{com}. 
. 
. **----------------------------------------------------------------------------**
. *** OUR DATA (NO POPULATION WEIGHTS)
. **----------------------------------------------------------------------------**
. preserve
{txt}
{com}. 
. replace D_housing_price_2=housing_price_growth_term_1 if D_housing_price_==.
{txt}(100 real changes made)

{com}. global controls_ours D_unemployment_rate_2 D_gdp_pc_2 D_housing_price_2 D_cpi_2
{txt}
{com}. 
. 
. rename top_prizes_gdp_term_2 dummy
{res}{txt}
{com}. rename expenditure_gdp_term_2 dummy2
{res}{txt}
{com}. rename top_prizes_gdp_term_1 top_prizes_gdp_term_2
{res}{txt}
{com}. rename expenditure_gdp_term_1 expenditure_gdp_term_2
{res}{txt}
{com}. 
. eststo col_4_89: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==1989

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     6.59
                                                {txt}Prob > F          = {res}    0.0001
                                                {txt}R-squared         = {res}    0.2852
                                                {txt}Root MSE          =    {res} 2.3361

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2}-.0106212{col 36}{space 2}  .118534{col 47}{space 1}   -0.09{col 56}{space 3}0.929{col 64}{space 4}-.2496679{col 77}{space 3} .2284254
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-1.394418{col 36}{space 2} 2.020713{col 47}{space 1}   -0.69{col 56}{space 3}0.494{col 64}{space 4}-5.469573{col 77}{space 3} 2.680737
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0731726{col 36}{space 2} .1342908{col 47}{space 1}    0.54{col 56}{space 3}0.589{col 64}{space 4}-.1976506{col 77}{space 3} .3439957
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0891942{col 36}{space 2}  .042391{col 47}{space 1}    2.10{col 56}{space 3}0.041{col 64}{space 4} .0037047{col 77}{space 3} .1746838
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0567056{col 36}{space 2} .0378521{col 47}{space 1}   -1.50{col 56}{space 3}0.141{col 64}{space 4}-.1330417{col 77}{space 3} .0196305
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.5707862{col 36}{space 2} .1700522{col 47}{space 1}   -3.36{col 56}{space 3}0.002{col 64}{space 4}-.9137292{col 77}{space 3}-.2278432
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}   8.7489{col 36}{space 2} 3.497361{col 47}{space 1}    2.50{col 56}{space 3}0.016{col 64}{space 4} 1.695799{col 77}{space 3}   15.802
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-2.6632372
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1989"

{txt}added macro:
           e(Election) : "{res:1989}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_93: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==1993

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     6.80
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.3756
                                                {txt}Root MSE          =    {res} 2.3375

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2}-2.335582{col 36}{space 2} .9131064{col 47}{space 1}   -2.56{col 56}{space 3}0.014{col 64}{space 4}-4.177037{col 77}{space 3}-.4941273
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} 2.527231{col 36}{space 2}  1.26287{col 47}{space 1}    2.00{col 56}{space 3}0.052{col 64}{space 4}  -.01959{col 77}{space 3} 5.074052
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} -.329501{col 36}{space 2} .1126861{col 47}{space 1}   -2.92{col 56}{space 3}0.005{col 64}{space 4}-.5567542{col 77}{space 3}-.1022479
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0927893{col 36}{space 2} .0441131{col 47}{space 1}    2.10{col 56}{space 3}0.041{col 64}{space 4} .0038269{col 77}{space 3} .1817518
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .2489419{col 36}{space 2} .0683029{col 47}{space 1}    3.64{col 56}{space 3}0.001{col 64}{space 4} .1111961{col 77}{space 3} .3866878
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .0451252{col 36}{space 2} .1321571{col 47}{space 1}    0.34{col 56}{space 3}0.734{col 64}{space 4}-.2213951{col 77}{space 3} .3116454
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} -3.64569{col 36}{space 2} 3.943051{col 47}{space 1}   -0.92{col 56}{space 3}0.360{col 64}{space 4}-11.59761{col 77}{space 3} 4.306231
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-.75916344
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1993"

{txt}added macro:
           e(Election) : "{res:1993}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_96: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==1996

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     5.35
                                                {txt}Prob > F          = {res}    0.0003
                                                {txt}R-squared         = {res}    0.2677
                                                {txt}Root MSE          =    {res} 2.6562

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} 1.260325{col 36}{space 2} .4530405{col 47}{space 1}    2.78{col 56}{space 3}0.008{col 64}{space 4} .3466819{col 77}{space 3} 2.173968
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-.3688473{col 36}{space 2}  1.63665{col 47}{space 1}   -0.23{col 56}{space 3}0.823{col 64}{space 4}-3.669466{col 77}{space 3} 2.931771
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0612627{col 36}{space 2} .1030938{col 47}{space 1}    0.59{col 56}{space 3}0.555{col 64}{space 4}-.1466458{col 77}{space 3} .2691713
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0779904{col 36}{space 2} .0474098{col 47}{space 1}    1.65{col 56}{space 3}0.107{col 64}{space 4}-.0176206{col 77}{space 3} .1736014
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .3714219{col 36}{space 2} .1070919{col 47}{space 1}    3.47{col 56}{space 3}0.001{col 64}{space 4} .1554505{col 77}{space 3} .5873933
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.1048715{col 36}{space 2} .3122367{col 47}{space 1}   -0.34{col 56}{space 3}0.739{col 64}{space 4}-.7345569{col 77}{space 3} .5248139
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 1.014507{col 36}{space 2} 4.787085{col 47}{space 1}    0.21{col 56}{space 3}0.833{col 64}{space 4}-8.639571{col 77}{space 3} 10.66858
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-1.1425475
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1996"

{txt}added macro:
           e(Election) : "{res:1996}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_00: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==2000

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.45
                                                {txt}Prob > F          = {res}    0.0396
                                                {txt}R-squared         = {res}    0.2010
                                                {txt}Root MSE          =    {res} 2.7753

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .7318108{col 36}{space 2} .6490069{col 47}{space 1}    1.13{col 56}{space 3}0.266{col 64}{space 4}-.5770363{col 77}{space 3} 2.040658
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-2.717708{col 36}{space 2} 1.482427{col 47}{space 1}   -1.83{col 56}{space 3}0.074{col 64}{space 4}-5.707307{col 77}{space 3} .2718911
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.1701421{col 36}{space 2} .1307162{col 47}{space 1}   -1.30{col 56}{space 3}0.200{col 64}{space 4}-.4337565{col 77}{space 3} .0934724
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.0104734{col 36}{space 2}  .027681{col 47}{space 1}   -0.38{col 56}{space 3}0.707{col 64}{space 4}-.0662975{col 77}{space 3} .0453508
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}  .008182{col 36}{space 2}  .040465{col 47}{space 1}    0.20{col 56}{space 3}0.841{col 64}{space 4}-.0734235{col 77}{space 3} .0897875
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .4418349{col 36}{space 2} .4155432{col 47}{space 1}    1.06{col 56}{space 3}0.294{col 64}{space 4}-.3961879{col 77}{space 3} 1.279858
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 2.860166{col 36}{space 2}  3.94981{col 47}{space 1}    0.72{col 56}{space 3}0.473{col 64}{space 4}-5.105384{col 77}{space 3} 10.82572
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}5.2046794
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2000"

{txt}added macro:
           e(Election) : "{res:2000}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_04: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==2004

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     1.23
                                                {txt}Prob > F          = {res}    0.3101
                                                {txt}R-squared         = {res}    0.1198
                                                {txt}Root MSE          =    {res} 2.5194

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .1896239{col 36}{space 2} .1887241{col 47}{space 1}    1.00{col 56}{space 3}0.321{col 64}{space 4}-.1909745{col 77}{space 3} .5702223
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} 1.406408{col 36}{space 2} 1.266588{col 47}{space 1}    1.11{col 56}{space 3}0.273{col 64}{space 4}-1.147911{col 77}{space 3} 3.960727
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.1230646{col 36}{space 2} .1220196{col 47}{space 1}   -1.01{col 56}{space 3}0.319{col 64}{space 4}-.3691405{col 77}{space 3} .1230114
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0141802{col 36}{space 2} .0739533{col 47}{space 1}    0.19{col 56}{space 3}0.849{col 64}{space 4}-.1349608{col 77}{space 3} .1633212
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0067436{col 36}{space 2} .0176989{col 47}{space 1}    0.38{col 56}{space 3}0.705{col 64}{space 4}-.0289497{col 77}{space 3} .0424368
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.1817691{col 36}{space 2} .4019607{col 47}{space 1}   -0.45{col 56}{space 3}0.653{col 64}{space 4}-.9924001{col 77}{space 3} .6288619
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-6.639996{col 36}{space 2} 4.672207{col 47}{space 1}   -1.42{col 56}{space 3}0.162{col 64}{space 4} -16.0624{col 77}{space 3} 2.782408
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-6.3910645
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2004"

{txt}added macro:
           e(Election) : "{res:2004}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_08: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==2008

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.05
                                                {txt}Prob > F          = {res}    0.0789
                                                {txt}R-squared         = {res}    0.1765
                                                {txt}Root MSE          =    {res}  4.156

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .3267113{col 36}{space 2} .1571321{col 47}{space 1}    2.08{col 56}{space 3}0.044{col 64}{space 4} .0098243{col 77}{space 3} .6435984
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-2.230746{col 36}{space 2} 2.024391{col 47}{space 1}   -1.10{col 56}{space 3}0.277{col 64}{space 4}-6.313319{col 77}{space 3} 1.851827
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.2762936{col 36}{space 2} .1756804{col 47}{space 1}   -1.57{col 56}{space 3}0.123{col 64}{space 4} -.630587{col 77}{space 3} .0779997
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.0021086{col 36}{space 2} .1536154{col 47}{space 1}   -0.01{col 56}{space 3}0.989{col 64}{space 4}-.3119037{col 77}{space 3} .3076865
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0440021{col 36}{space 2} .0536636{col 47}{space 1}   -0.82{col 56}{space 3}0.417{col 64}{space 4}-.1522249{col 77}{space 3} .0642208
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .7223738{col 36}{space 2}  .733307{col 47}{space 1}    0.99{col 56}{space 3}0.330{col 64}{space 4}-.7564807{col 77}{space 3} 2.201228
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-1.964709{col 36}{space 2} 9.751669{col 47}{space 1}   -0.20{col 56}{space 3}0.841{col 64}{space 4}-21.63082{col 77}{space 3} 17.70141
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}2.1097373
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2008"

{txt}added macro:
           e(Election) : "{res:2008}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. 
. rename expenditure_gdp_term_2 expenditure_gdp_term_1 
{res}{txt}
{com}. rename top_prizes_gdp_term_2 top_prizes_gdp_term_1 
{res}{txt}
{com}. rename dummy2 expenditure_gdp_term_2 
{res}{txt}
{com}. rename dummy top_prizes_gdp_term_2 
{res}{txt}
{com}. 
. 
. eststo col_4_11: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==2011

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}    12.01
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.2627
                                                {txt}Root MSE          =    {res} 1.9578

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2}-.1472762{col 36}{space 2} .4821797{col 47}{space 1}   -0.31{col 56}{space 3}0.762{col 64}{space 4}-1.119684{col 77}{space 3} .8251318
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} 2.828012{col 36}{space 2} 1.351586{col 47}{space 1}    2.09{col 56}{space 3}0.042{col 64}{space 4}  .102279{col 77}{space 3} 5.553745
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0694898{col 36}{space 2} .1119723{col 47}{space 1}    0.62{col 56}{space 3}0.538{col 64}{space 4}-.1563238{col 77}{space 3} .2953035
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.1172917{col 36}{space 2} .0874987{col 47}{space 1}   -1.34{col 56}{space 3}0.187{col 64}{space 4}-.2937496{col 77}{space 3} .0591662
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0925015{col 36}{space 2} .0466919{col 47}{space 1}    1.98{col 56}{space 3}0.054{col 64}{space 4}-.0016617{col 77}{space 3} .1866648
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.6323502{col 36}{space 2} .3646703{col 47}{space 1}   -1.73{col 56}{space 3}0.090{col 64}{space 4}-1.367778{col 77}{space 3} .1030775
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-12.68102{col 36}{space 2} 2.766096{col 47}{space 1}   -4.58{col 56}{space 3}0.000{col 64}{space 4}-18.25938{col 77}{space 3}-7.102652
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-14.61119
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2011"

{txt}added macro:
           e(Election) : "{res:2011}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_15: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==2015

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     3.57
                                                {txt}Prob > F          = {res}    0.0059
                                                {txt}R-squared         = {res}    0.2381
                                                {txt}Root MSE          =    {res} 4.0658

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .0361693{col 36}{space 2} .3932006{col 47}{space 1}    0.09{col 56}{space 3}0.927{col 64}{space 4}-.7567953{col 77}{space 3} .8291338
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-.9438231{col 36}{space 2} 1.395366{col 47}{space 1}   -0.68{col 56}{space 3}0.502{col 64}{space 4}-3.757847{col 77}{space 3}   1.8702
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .6038396{col 36}{space 2} .2110246{col 47}{space 1}    2.86{col 56}{space 3}0.006{col 64}{space 4}  .178268{col 77}{space 3} 1.029411
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0629021{col 36}{space 2} .1715267{col 47}{space 1}    0.37{col 56}{space 3}0.716{col 64}{space 4}-.2830146{col 77}{space 3} .4088187
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0221692{col 36}{space 2} .0958581{col 47}{space 1}   -0.23{col 56}{space 3}0.818{col 64}{space 4}-.2154854{col 77}{space 3} .1711471
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} 2.107747{col 36}{space 2} .8863671{col 47}{space 1}    2.38{col 56}{space 3}0.022{col 64}{space 4} .3202175{col 77}{space 3} 3.895277
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}  -17.467{col 36}{space 2} 2.387682{col 47}{space 1}   -7.32{col 56}{space 3}0.000{col 64}{space 4}-22.28222{col 77}{space 3}-12.65178
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-15.111396
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2015"

{txt}added macro:
           e(Election) : "{res:2015}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_16: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==2016

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     3.15
                                                {txt}Prob > F          = {res}    0.0118
                                                {txt}R-squared         = {res}    0.2262
                                                {txt}Root MSE          =    {res} 1.1778

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .1999002{col 36}{space 2} .1544842{col 47}{space 1}    1.29{col 56}{space 3}0.203{col 64}{space 4}-.1116469{col 77}{space 3} .5114473
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} 3.837784{col 36}{space 2} 1.217568{col 47}{space 1}    3.15{col 56}{space 3}0.003{col 64}{space 4} 1.382324{col 77}{space 3} 6.293243
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.0715215{col 36}{space 2} .0864349{col 47}{space 1}   -0.83{col 56}{space 3}0.413{col 64}{space 4}-.2458342{col 77}{space 3} .1027911
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}  .059064{col 36}{space 2} .0867981{col 47}{space 1}    0.68{col 56}{space 3}0.500{col 64}{space 4} -.115981{col 77}{space 3} .2341089
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0241291{col 36}{space 2}  .045372{col 47}{space 1}   -0.53{col 56}{space 3}0.598{col 64}{space 4}-.1156304{col 77}{space 3} .0673723
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} -1.51833{col 36}{space 2} .8637322{col 47}{space 1}   -1.76{col 56}{space 3}0.086{col 64}{space 4}-3.260212{col 77}{space 3} .2235523
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 5.261351{col 36}{space 2}  1.54196{col 47}{space 1}    3.41{col 56}{space 3}0.001{col 64}{space 4} 2.151692{col 77}{space 3} 8.371011
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}4.318167
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2016"

{txt}added macro:
           e(Election) : "{res:2016}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_19_4: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==2019 & month==4

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.72
                                                {txt}Prob > F          = {res}    0.0249
                                                {txt}R-squared         = {res}    0.1917
                                                {txt}Root MSE          =    {res} 2.0355

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .1739712{col 36}{space 2}  .338817{col 47}{space 1}    0.51{col 56}{space 3}0.610{col 64}{space 4}-.5093184{col 77}{space 3} .8572608
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} .6981562{col 36}{space 2}  2.14191{col 47}{space 1}    0.33{col 56}{space 3}0.746{col 64}{space 4}-3.621416{col 77}{space 3} 5.017728
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .3592978{col 36}{space 2}  .101049{col 47}{space 1}    3.56{col 56}{space 3}0.001{col 64}{space 4} .1555131{col 77}{space 3} .5630825
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0328773{col 36}{space 2} .0983073{col 47}{space 1}    0.33{col 56}{space 3}0.740{col 64}{space 4}-.1653782{col 77}{space 3} .2311329
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0534819{col 36}{space 2} .0418109{col 47}{space 1}    1.28{col 56}{space 3}0.208{col 64}{space 4}-.0308378{col 77}{space 3} .1378015
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .4713163{col 36}{space 2} .6511905{col 47}{space 1}    0.72{col 56}{space 3}0.473{col 64}{space 4}-.8419345{col 77}{space 3} 1.784567
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 4.944903{col 36}{space 2} 2.277012{col 47}{space 1}    2.17{col 56}{space 3}0.035{col 64}{space 4} .3528713{col 77}{space 3} 9.536934
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}5.7350554
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2019 (4)"

{txt}added macro:
           e(Election) : "{res:2019 (4)}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_19_11: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==2019 & month==11

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     6.42
                                                {txt}Prob > F          = {res}    0.0001
                                                {txt}R-squared         = {res}    0.3238
                                                {txt}Root MSE          =    {res} 1.4487

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .0081948{col 36}{space 2} .6335938{col 47}{space 1}    0.01{col 56}{space 3}0.990{col 64}{space 4}-1.269569{col 77}{space 3} 1.285958
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} 4.348721{col 36}{space 2} 2.208262{col 47}{space 1}    1.97{col 56}{space 3}0.055{col 64}{space 4}-.1046639{col 77}{space 3} 8.802105
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0328497{col 36}{space 2} .0868753{col 47}{space 1}    0.38{col 56}{space 3}0.707{col 64}{space 4}-.1423512{col 77}{space 3} .2080505
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .1191345{col 36}{space 2} .0527986{col 47}{space 1}    2.26{col 56}{space 3}0.029{col 64}{space 4}  .012656{col 77}{space 3}  .225613
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0599944{col 36}{space 2} .0716438{col 47}{space 1}   -0.84{col 56}{space 3}0.407{col 64}{space 4}-.2044779{col 77}{space 3} .0844891
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.3960247{col 36}{space 2} .3482482{col 47}{space 1}   -1.14{col 56}{space 3}0.262{col 64}{space 4}-1.098334{col 77}{space 3} .3062847
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-.2294099{col 36}{space 2}  1.29704{col 47}{space 1}   -0.18{col 56}{space 3}0.860{col 64}{space 4}-2.845141{col 77}{space 3} 2.386321
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-.16204425
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2019 (11)"

{txt}added macro:
           e(Election) : "{res:2019 (11)}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_23: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours, robust , if year==2023

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     4.05
                                                {txt}Prob > F          = {res}    0.0026
                                                {txt}R-squared         = {res}    0.3176
                                                {txt}Root MSE          =    {res} 3.7559

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .3250499{col 36}{space 2} 1.135645{col 47}{space 1}    0.29{col 56}{space 3}0.776{col 64}{space 4}-1.965196{col 77}{space 3} 2.615295
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-2.542869{col 36}{space 2}  .974045{col 47}{space 1}   -2.61{col 56}{space 3}0.012{col 64}{space 4}-4.507218{col 77}{space 3}-.5785197
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .1464029{col 36}{space 2} .2146484{col 47}{space 1}    0.68{col 56}{space 3}0.499{col 64}{space 4}-.2864768{col 77}{space 3} .5792827
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.1888588{col 36}{space 2} .1448278{col 47}{space 1}   -1.30{col 56}{space 3}0.199{col 64}{space 4} -.480932{col 77}{space 3} .1032144
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0258248{col 36}{space 2} .0710227{col 47}{space 1}   -0.36{col 56}{space 3}0.718{col 64}{space 4}-.1690558{col 77}{space 3} .1174061
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-1.123435{col 36}{space 2} .6422351{col 47}{space 1}   -1.75{col 56}{space 3}0.087{col 64}{space 4}-2.418625{col 77}{space 3} .1717556
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 19.64128{col 36}{space 2} 8.724268{col 47}{space 1}    2.25{col 56}{space 3}0.030{col 64}{space 4} 2.047115{col 77}{space 3} 37.23544
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}2.4617514
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2023"

{txt}added macro:
           e(Election) : "{res:2023}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_all: reg var_votes_inc_ours top_prizes_gdp_term_2 c.expenditure_gdp_term_2##i.year $controls_ours i.province_num, robust

{txt}Linear regression                               Number of obs     = {res}       600
                                                {txt}F(75, 524)        =  {res}    52.20
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8459
                                                {txt}Root MSE          =    {res} 3.0879

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}           var_votes_inc_ours{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}top_prizes_gdp_term_2 {c |}{col 31}{res}{space 2}  .272772{col 43}{space 2} .0957239{col 54}{space 1}    2.85{col 63}{space 3}0.005{col 71}{space 4} .0847222{col 84}{space 3} .4608219
{txt}{space 7}expenditure_gdp_term_2 {c |}{col 31}{res}{space 2}-3.452587{col 43}{space 2} 2.553733{col 54}{space 1}   -1.35{col 63}{space 3}0.177{col 71}{space 4}-8.469399{col 84}{space 3} 1.564225
{txt}{space 29} {c |}
{space 25}year {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} 2.766749{col 43}{space 2} 2.327051{col 54}{space 1}    1.19{col 63}{space 3}0.235{col 71}{space 4}-1.804745{col 84}{space 3} 7.338244
{txt}{space 24}1996  {c |}{col 31}{res}{space 2}-.2839907{col 43}{space 2} 2.101007{col 54}{space 1}   -0.14{col 63}{space 3}0.893{col 71}{space 4}-4.411422{col 84}{space 3}  3.84344
{txt}{space 24}2000  {c |}{col 31}{res}{space 2} 6.819104{col 43}{space 2} 2.464699{col 54}{space 1}    2.77{col 63}{space 3}0.006{col 71}{space 4}   1.9772{col 84}{space 3} 11.66101
{txt}{space 24}2004  {c |}{col 31}{res}{space 2}-8.737078{col 43}{space 2} 2.446797{col 54}{space 1}   -3.57{col 63}{space 3}0.000{col 71}{space 4}-13.54381{col 84}{space 3}-3.930342
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} 4.526565{col 43}{space 2} 2.788648{col 54}{space 1}    1.62{col 63}{space 3}0.105{col 71}{space 4}-.9517383{col 84}{space 3} 10.00487
{txt}{space 24}2011  {c |}{col 31}{res}{space 2}-16.68541{col 43}{space 2} 2.661634{col 54}{space 1}   -6.27{col 63}{space 3}0.000{col 71}{space 4}-21.91419{col 84}{space 3}-11.45662
{txt}{space 24}2015  {c |}{col 31}{res}{space 2} -17.4944{col 43}{space 2} 3.016161{col 54}{space 1}   -5.80{col 63}{space 3}0.000{col 71}{space 4}-23.41965{col 84}{space 3}-11.56914
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} .0749534{col 43}{space 2} 2.792183{col 54}{space 1}    0.03{col 63}{space 3}0.979{col 71}{space 4}-5.410294{col 84}{space 3}   5.5602
{txt}{space 24}2019  {c |}{col 31}{res}{space 2} -1.81831{col 43}{space 2} 2.733317{col 54}{space 1}   -0.67{col 63}{space 3}0.506{col 71}{space 4}-7.187915{col 84}{space 3} 3.551295
{txt}{space 24}2023  {c |}{col 31}{res}{space 2} 6.682807{col 43}{space 2} 2.315659{col 54}{space 1}    2.89{col 63}{space 3}0.004{col 71}{space 4} 2.133691{col 84}{space 3} 11.23192
{txt}{space 29} {c |}
year#c.expenditure_gdp_term_2 {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} 3.408516{col 43}{space 2} 2.523085{col 54}{space 1}    1.35{col 63}{space 3}0.177{col 71}{space 4} -1.54809{col 84}{space 3} 8.365121
{txt}{space 24}1996  {c |}{col 31}{res}{space 2} 2.205902{col 43}{space 2} 2.525224{col 54}{space 1}    0.87{col 63}{space 3}0.383{col 71}{space 4}-2.754905{col 84}{space 3} 7.166708
{txt}{space 24}2000  {c |}{col 31}{res}{space 2}-.0817911{col 43}{space 2} 2.494099{col 54}{space 1}   -0.03{col 63}{space 3}0.974{col 71}{space 4}-4.981452{col 84}{space 3} 4.817869
{txt}{space 24}2004  {c |}{col 31}{res}{space 2}  4.02726{col 43}{space 2} 2.488282{col 54}{space 1}    1.62{col 63}{space 3}0.106{col 71}{space 4}-.8609743{col 84}{space 3} 8.915494
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} .6475016{col 43}{space 2} 2.615952{col 54}{space 1}    0.25{col 63}{space 3}0.805{col 71}{space 4} -4.49154{col 84}{space 3} 5.786543
{txt}{space 24}2011  {c |}{col 31}{res}{space 2}  4.28653{col 43}{space 2}  2.48877{col 54}{space 1}    1.72{col 63}{space 3}0.086{col 71}{space 4}-.6026624{col 84}{space 3} 9.175722
{txt}{space 24}2015  {c |}{col 31}{res}{space 2} 2.558496{col 43}{space 2} 2.518316{col 54}{space 1}    1.02{col 63}{space 3}0.310{col 71}{space 4}-2.388739{col 84}{space 3}  7.50573
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} 4.880715{col 43}{space 2} 3.528778{col 54}{space 1}    1.38{col 63}{space 3}0.167{col 71}{space 4}-2.051574{col 84}{space 3}   11.813
{txt}{space 24}2019  {c |}{col 31}{res}{space 2} 6.457087{col 43}{space 2} 4.017941{col 54}{space 1}    1.61{col 63}{space 3}0.109{col 71}{space 4}-1.436165{col 84}{space 3} 14.35034
{txt}{space 24}2023  {c |}{col 31}{res}{space 2}-.6429092{col 43}{space 2}  2.47868{col 54}{space 1}   -0.26{col 63}{space 3}0.795{col 71}{space 4}-5.512279{col 84}{space 3} 4.226461
{txt}{space 29} {c |}
{space 8}D_unemployment_rate_2 {c |}{col 31}{res}{space 2}-.0475132{col 43}{space 2} .0472198{col 54}{space 1}   -1.01{col 63}{space 3}0.315{col 71}{space 4}-.1402766{col 84}{space 3} .0452502
{txt}{space 19}D_gdp_pc_2 {c |}{col 31}{res}{space 2} .0176003{col 43}{space 2} .0195331{col 54}{space 1}    0.90{col 63}{space 3}0.368{col 71}{space 4}-.0207725{col 84}{space 3}  .055973
{txt}{space 12}D_housing_price_2 {c |}{col 31}{res}{space 2} .0217899{col 43}{space 2} .0151708{col 54}{space 1}    1.44{col 63}{space 3}0.152{col 71}{space 4}-.0080131{col 84}{space 3} .0515929
{txt}{space 22}D_cpi_2 {c |}{col 31}{res}{space 2}-.2982231{col 43}{space 2} .1254319{col 54}{space 1}   -2.38{col 63}{space 3}0.018{col 71}{space 4}-.5446344{col 84}{space 3}-.0518119
{txt}{space 29} {c |}
{space 17}province_num {c |}
{space 23}alava  {c |}{col 31}{res}{space 2} .6199471{col 43}{space 2} 1.631928{col 54}{space 1}    0.38{col 63}{space 3}0.704{col 71}{space 4}-2.585978{col 84}{space 3} 3.825872
{txt}{space 20}albacete  {c |}{col 31}{res}{space 2}-.3558329{col 43}{space 2} 1.008654{col 54}{space 1}   -0.35{col 63}{space 3}0.724{col 71}{space 4}-2.337335{col 84}{space 3} 1.625669
{txt}{space 20}alicante  {c |}{col 31}{res}{space 2}-.4092822{col 43}{space 2} 1.283342{col 54}{space 1}   -0.32{col 63}{space 3}0.750{col 71}{space 4}-2.930409{col 84}{space 3} 2.111845
{txt}{space 21}almeria  {c |}{col 31}{res}{space 2}-1.393363{col 43}{space 2} 1.346707{col 54}{space 1}   -1.03{col 63}{space 3}0.301{col 71}{space 4}-4.038971{col 84}{space 3} 1.252245
{txt}{space 20}asturias  {c |}{col 31}{res}{space 2} 1.303236{col 43}{space 2} 1.421886{col 54}{space 1}    0.92{col 63}{space 3}0.360{col 71}{space 4}-1.490062{col 84}{space 3} 4.096534
{txt}{space 23}avila  {c |}{col 31}{res}{space 2} 1.665475{col 43}{space 2} 1.121373{col 54}{space 1}    1.49{col 63}{space 3}0.138{col 71}{space 4}-.5374645{col 84}{space 3} 3.868414
{txt}{space 21}badajoz  {c |}{col 31}{res}{space 2}-.8978622{col 43}{space 2}  1.04088{col 54}{space 1}   -0.86{col 63}{space 3}0.389{col 71}{space 4}-2.942673{col 84}{space 3} 1.146949
{txt}{space 19}barcelona  {c |}{col 31}{res}{space 2} 1.268772{col 43}{space 2} 1.561327{col 54}{space 1}    0.81{col 63}{space 3}0.417{col 71}{space 4}-1.798457{col 84}{space 3}    4.336
{txt}{space 22}burgos  {c |}{col 31}{res}{space 2} .5083591{col 43}{space 2} 1.054843{col 54}{space 1}    0.48{col 63}{space 3}0.630{col 71}{space 4}-1.563881{col 84}{space 3} 2.580599
{txt}{space 21}caceres  {c |}{col 31}{res}{space 2}-.1481192{col 43}{space 2} .9663112{col 54}{space 1}   -0.15{col 63}{space 3}0.878{col 71}{space 4}-2.046439{col 84}{space 3} 1.750201
{txt}{space 23}cadiz  {c |}{col 31}{res}{space 2} -2.74711{col 43}{space 2} 1.209785{col 54}{space 1}   -2.27{col 63}{space 3}0.024{col 71}{space 4}-5.123735{col 84}{space 3}-.3704852
{txt}{space 19}cantabria  {c |}{col 31}{res}{space 2}-.1938409{col 43}{space 2} 1.245491{col 54}{space 1}   -0.16{col 63}{space 3}0.876{col 71}{space 4} -2.64061{col 84}{space 3} 2.252929
{txt}{space 19}castellon  {c |}{col 31}{res}{space 2}-.3652068{col 43}{space 2} 1.200439{col 54}{space 1}   -0.30{col 63}{space 3}0.761{col 71}{space 4}-2.723471{col 84}{space 3} 1.993058
{txt}{space 17}ciudad real  {c |}{col 31}{res}{space 2} .0474937{col 43}{space 2}  1.13301{col 54}{space 1}    0.04{col 63}{space 3}0.967{col 71}{space 4}-2.178306{col 84}{space 3} 2.273293
{txt}{space 21}cordoba  {c |}{col 31}{res}{space 2}-.8286944{col 43}{space 2} 1.047054{col 54}{space 1}   -0.79{col 63}{space 3}0.429{col 71}{space 4}-2.885633{col 84}{space 3} 1.228244
{txt}{space 22}cuenca  {c |}{col 31}{res}{space 2} .8470642{col 43}{space 2} 1.127775{col 54}{space 1}    0.75{col 63}{space 3}0.453{col 71}{space 4}-1.368451{col 84}{space 3} 3.062579
{txt}{space 20}gipuzkoa  {c |}{col 31}{res}{space 2} 1.623861{col 43}{space 2} 1.816207{col 54}{space 1}    0.89{col 63}{space 3}0.372{col 71}{space 4} -1.94408{col 84}{space 3} 5.191802
{txt}{space 22}girona  {c |}{col 31}{res}{space 2} 2.048283{col 43}{space 2} 1.678866{col 54}{space 1}    1.22{col 63}{space 3}0.223{col 71}{space 4}-1.249851{col 84}{space 3} 5.346418
{txt}{space 21}granada  {c |}{col 31}{res}{space 2}-.8999557{col 43}{space 2} 1.007929{col 54}{space 1}   -0.89{col 63}{space 3}0.372{col 71}{space 4}-2.880034{col 84}{space 3} 1.080123
{txt}{space 17}guadalajara  {c |}{col 31}{res}{space 2}-.6230758{col 43}{space 2} 1.115063{col 54}{space 1}   -0.56{col 63}{space 3}0.577{col 71}{space 4}-2.813618{col 84}{space 3} 1.567467
{txt}{space 22}huelva  {c |}{col 31}{res}{space 2} -2.20696{col 43}{space 2} 1.244044{col 54}{space 1}   -1.77{col 63}{space 3}0.077{col 71}{space 4}-4.650886{col 84}{space 3} .2369665
{txt}{space 22}huesca  {c |}{col 31}{res}{space 2}-.3411148{col 43}{space 2} 1.177873{col 54}{space 1}   -0.29{col 63}{space 3}0.772{col 71}{space 4}-2.655048{col 84}{space 3} 1.972819
{txt}{space 14}islas baleares  {c |}{col 31}{res}{space 2}-.3687216{col 43}{space 2} 1.309885{col 54}{space 1}   -0.28{col 63}{space 3}0.778{col 71}{space 4}-2.941993{col 84}{space 3} 2.204549
{txt}{space 24}jaen  {c |}{col 31}{res}{space 2}-1.081513{col 43}{space 2} 1.056604{col 54}{space 1}   -1.02{col 63}{space 3}0.307{col 71}{space 4}-3.157213{col 84}{space 3} .9941866
{txt}{space 20}la rioja  {c |}{col 31}{res}{space 2} .6387099{col 43}{space 2} .9856574{col 54}{space 1}    0.65{col 63}{space 3}0.517{col 71}{space 4}-1.297616{col 84}{space 3} 2.575035
{txt}{space 18}las palmas  {c |}{col 31}{res}{space 2}-.7905573{col 43}{space 2} 1.511388{col 54}{space 1}   -0.52{col 63}{space 3}0.601{col 71}{space 4}-3.759681{col 84}{space 3} 2.178566
{txt}{space 24}leon  {c |}{col 31}{res}{space 2} -.037365{col 43}{space 2} 1.093022{col 54}{space 1}   -0.03{col 63}{space 3}0.973{col 71}{space 4}-2.184609{col 84}{space 3} 2.109879
{txt}{space 22}lleida  {c |}{col 31}{res}{space 2} 2.651741{col 43}{space 2} 1.882103{col 54}{space 1}    1.41{col 63}{space 3}0.159{col 71}{space 4}-1.045653{col 84}{space 3} 6.349134
{txt}{space 24}lugo  {c |}{col 31}{res}{space 2} .7336559{col 43}{space 2} 1.259458{col 54}{space 1}    0.58{col 63}{space 3}0.560{col 71}{space 4} -1.74055{col 84}{space 3} 3.207862
{txt}{space 22}madrid  {c |}{col 31}{res}{space 2}-1.222327{col 43}{space 2} 1.284886{col 54}{space 1}   -0.95{col 63}{space 3}0.342{col 71}{space 4}-3.746488{col 84}{space 3} 1.301833
{txt}{space 22}malaga  {c |}{col 31}{res}{space 2}-2.399045{col 43}{space 2} 1.123651{col 54}{space 1}   -2.14{col 63}{space 3}0.033{col 71}{space 4} -4.60646{col 84}{space 3}-.1916304
{txt}{space 22}murcia  {c |}{col 31}{res}{space 2}-.4907373{col 43}{space 2} 1.526829{col 54}{space 1}   -0.32{col 63}{space 3}0.748{col 71}{space 4}-3.490195{col 84}{space 3}  2.50872
{txt}{space 21}navarra  {c |}{col 31}{res}{space 2} .6458019{col 43}{space 2}  1.59514{col 54}{space 1}    0.40{col 63}{space 3}0.686{col 71}{space 4}-2.487852{col 84}{space 3} 3.779456
{txt}{space 21}ourense  {c |}{col 31}{res}{space 2} 2.058811{col 43}{space 2} 1.454302{col 54}{space 1}    1.42{col 63}{space 3}0.157{col 71}{space 4}-.7981669{col 84}{space 3} 4.915789
{txt}{space 20}palencia  {c |}{col 31}{res}{space 2} .8460954{col 43}{space 2} 1.008352{col 54}{space 1}    0.84{col 63}{space 3}0.402{col 71}{space 4}-1.134813{col 84}{space 3} 2.827004
{txt}{space 18}pontevedra  {c |}{col 31}{res}{space 2} .4619766{col 43}{space 2}  1.21751{col 54}{space 1}    0.38{col 63}{space 3}0.705{col 71}{space 4}-1.929823{col 84}{space 3} 2.853776
{txt}{space 19}salamanca  {c |}{col 31}{res}{space 2}-.0342745{col 43}{space 2} 1.032531{col 54}{space 1}   -0.03{col 63}{space 3}0.974{col 71}{space 4}-2.062683{col 84}{space 3} 1.994134
{txt}{space 6}santa cruz de tenerife  {c |}{col 31}{res}{space 2}-.0732087{col 43}{space 2} 1.117092{col 54}{space 1}   -0.07{col 63}{space 3}0.948{col 71}{space 4}-2.267738{col 84}{space 3}  2.12132
{txt}{space 21}segovia  {c |}{col 31}{res}{space 2}  .734319{col 43}{space 2} 1.137178{col 54}{space 1}    0.65{col 63}{space 3}0.519{col 71}{space 4}-1.499669{col 84}{space 3} 2.968307
{txt}{space 21}sevilla  {c |}{col 31}{res}{space 2}-1.607238{col 43}{space 2} 1.236305{col 54}{space 1}   -1.30{col 63}{space 3}0.194{col 71}{space 4} -4.03596{col 84}{space 3}  .821485
{txt}{space 23}soria  {c |}{col 31}{res}{space 2} .5819264{col 43}{space 2} 1.697461{col 54}{space 1}    0.34{col 63}{space 3}0.732{col 71}{space 4}-2.752738{col 84}{space 3}  3.91659
{txt}{space 19}tarragona  {c |}{col 31}{res}{space 2} .9114942{col 43}{space 2} 1.616177{col 54}{space 1}    0.56{col 63}{space 3}0.573{col 71}{space 4}-2.263488{col 84}{space 3} 4.086477
{txt}{space 22}teruel  {c |}{col 31}{res}{space 2}-.2208719{col 43}{space 2} 1.515945{col 54}{space 1}   -0.15{col 63}{space 3}0.884{col 71}{space 4}-3.198947{col 84}{space 3} 2.757204
{txt}{space 22}toledo  {c |}{col 31}{res}{space 2}-.4957314{col 43}{space 2} 1.100786{col 54}{space 1}   -0.45{col 63}{space 3}0.653{col 71}{space 4}-2.658227{col 84}{space 3} 1.666764
{txt}{space 20}valencia  {c |}{col 31}{res}{space 2}-.2313838{col 43}{space 2} 1.306771{col 54}{space 1}   -0.18{col 63}{space 3}0.860{col 71}{space 4}-2.798537{col 84}{space 3} 2.335769
{txt}{space 18}valladolid  {c |}{col 31}{res}{space 2}-.2155673{col 43}{space 2} 1.052917{col 54}{space 1}   -0.20{col 63}{space 3}0.838{col 71}{space 4}-2.284025{col 84}{space 3}  1.85289
{txt}{space 21}vizcaya  {c |}{col 31}{res}{space 2} 1.989491{col 43}{space 2} 1.593271{col 54}{space 1}    1.25{col 63}{space 3}0.212{col 71}{space 4}-1.140491{col 84}{space 3} 5.119474
{txt}{space 22}zamora  {c |}{col 31}{res}{space 2} 1.034335{col 43}{space 2} 1.032844{col 54}{space 1}    1.00{col 63}{space 3}0.317{col 71}{space 4}-.9946873{col 84}{space 3} 3.063358
{txt}{space 20}zaragoza  {c |}{col 31}{res}{space 2}-1.314305{col 43}{space 2}  1.33077{col 54}{space 1}   -0.99{col 63}{space 3}0.324{col 71}{space 4}-3.928605{col 84}{space 3} 1.299996
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2}  4.03804{col 43}{space 2} 3.094263{col 54}{space 1}    1.31{col 63}{space 3}0.192{col 71}{space 4}-2.040644{col 84}{space 3} 10.11672
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-1.7509378
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "All"

{txt}added macro:
           e(Election) : "{res:All}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_meta: reg var_votes_inc_ours var_votes_inc_ours

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       600
{txt}{hline 13}{c +}{hline 34}   F(1, 598)       = {res}        .
{txt}       Model {c |} {res} 32423.3892         1  32423.3892   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res}          0       598           0   {txt}R-squared       ={res}    1.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    1.0000
{txt}       Total {c |} {res} 32423.3892       599  54.1291974   {txt}Root MSE        =   {res}      0

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}var_votes_inc_ours{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var_votes_inc_ours {c |}{col 20}{res}{space 2}        1{col 32}{space 2}        .{col 43}{space 1}       .{col 52}{space 3}    .{col 60}{space 4}        .{col 73}{space 3}        .
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 4.44e-16{col 32}{space 2}        .{col 43}{space 1}       .{col 52}{space 3}    .{col 60}{space 4}        .{col 73}{space 3}        .
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-1.7509378
{txt}
{com}. estadd local Estimation "Meta"

{txt}added macro:
         e(Estimation) : "{res:Meta}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year ""

{txt}added macro:
               e(Year) : "{res:}"

{com}. estadd local Province ""

{txt}added macro:
           e(Province) : "{res:}"

{com}. estadd local Cluster ""

{txt}added macro:
            e(Cluster) : "{res:}"

{com}. estadd local Controls ""

{txt}added macro:
           e(Controls) : "{res:}"

{com}. estadd local Election "All"

{txt}added macro:
           e(Election) : "{res:All}"

{com}. estadd local Pop_weights ""

{txt}added macro:
        e(Pop_weights) : "{res:}"

{com}. 
. 
. * Table A8 - Electoral Results without Population Weights, by Election, Using Our Data
. esttab col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 col_4_all col_4_meta using ${c -(}tables{c )-}electoral_results_our_data_by_election_inter.tex, ///
>                 keep(top_prizes_gdp_term_2)  ///
>                 nocon r2 ///
>                 mtitles se mtitles("Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." ///
>                                                         "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." ///
>                                                         "Vote Incumb." "Vote Incumb.")  ///
>                 coeflabels(top_prizes_gdp_term_2 "Cumulative Top Prizes")  ///
>                                         scalars("MeanDV Outcome Mean" "Estimation Estimation" "Data Data" "Year Year FEs" "Province Province FEs" "Controls Controls" "Cluster Cluster Province" "Election Election" "Pop_weights Pop. Weights")  ///
>         star(* 0.05 ** 0.01) b(%9.3f) replace
{res}{txt}(note: file Results/Tables_Electoral/electoral_results_our_data_by_election_inter.tex not found)
(output written to {browse  `"Results/Tables_Electoral/electoral_results_our_data_by_election_inter.tex"'})

{com}.                 
. 
. **----------------------------------------------------------------------------**
. *** META ANALYSIS (NO POPULATION WEIGHTS)
. **----------------------------------------------------------------------------**
. 
. * Pooled
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_term_2]
{txt}  4{com}.     local se = _se[top_prizes_gdp_term_2]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_89:col_4_89} are active now)
(results {stata estimates replay col_4_93:col_4_93} are active now)
(results {stata estimates replay col_4_96:col_4_96} are active now)
(results {stata estimates replay col_4_00:col_4_00} are active now)
(results {stata estimates replay col_4_04:col_4_04} are active now)
(results {stata estimates replay col_4_08:col_4_08} are active now)
(results {stata estimates replay col_4_11:col_4_11} are active now)
(results {stata estimates replay col_4_15:col_4_15} are active now)
(results {stata estimates replay col_4_16:col_4_16} are active now)
(results {stata estimates replay col_4_19_4:col_4_19_4} are active now)
(results {stata estimates replay col_4_19_11:col_4_19_11} are active now)
(results {stata estimates replay col_4_23:col_4_23} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient
{res}{txt}
{com}. rename c2 stderr
{res}{txt}
{com}. 
. gen regression = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
variable {bf}regression{sf} was {bf}{res}str8{sf}{txt} now {bf}{res}str10{sf}
{txt}(1 real change made)
variable {bf}regression{sf} was {bf}{res}str10{sf}{txt} now {bf}{res}str11{sf}
{txt}(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient stderr , studylabel(regression)
{txt}(638 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}12
{col 8}{txt}Study label:  {res}regression
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient
{txt}{col 11}Std. Err.:  {res}stderr
{txt}{col 9}Study label:  {res}regression

{txt}Meta-analysis summary{col 43}Number of studies = {res}    12
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 0.0074
{txt}{col 53}I2 (%) = {res}  10.19
{txt}{col 57}H2 = {res}   1.11

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_89{col 19}{c |}{res}{space 6}   -0.011{col 35}{space 3}   -0.243{col 47}{space 3}    0.222{col 59}{space 5}28.60
{col 1}{txt}         col_4_93{col 19}{c |}{res}{space 6}   -2.336{col 35}{space 3}   -4.125{col 47}{space 3}   -0.546{col 59}{space 5} 0.73
{col 1}{txt}         col_4_96{col 19}{c |}{res}{space 6}    1.260{col 35}{space 3}    0.372{col 47}{space 3}    2.148{col 59}{space 5} 2.89
{col 1}{txt}         col_4_00{col 19}{c |}{res}{space 6}    0.732{col 35}{space 3}   -0.540{col 47}{space 3}    2.004{col 59}{space 5} 1.43
{col 1}{txt}         col_4_04{col 19}{c |}{res}{space 6}    0.190{col 35}{space 3}   -0.180{col 47}{space 3}    0.560{col 59}{space 5}14.26
{col 1}{txt}         col_4_08{col 19}{c |}{res}{space 6}    0.327{col 35}{space 3}    0.019{col 47}{space 3}    0.635{col 59}{space 5}19.12
{col 1}{txt}         col_4_11{col 19}{c |}{res}{space 6}   -0.147{col 35}{space 3}   -1.092{col 47}{space 3}    0.798{col 59}{space 5} 2.56
{col 1}{txt}         col_4_15{col 19}{c |}{res}{space 6}    0.036{col 35}{space 3}   -0.734{col 47}{space 3}    0.807{col 59}{space 5} 3.79
{col 1}{txt}         col_4_16{col 19}{c |}{res}{space 6}    0.200{col 35}{space 3}   -0.103{col 47}{space 3}    0.503{col 59}{space 5}19.62
{col 1}{txt}       col_4_19_4{col 19}{c |}{res}{space 6}    0.174{col 35}{space 3}   -0.490{col 47}{space 3}    0.838{col 59}{space 5} 5.02
{col 1}{txt}      col_4_19_11{col 19}{c |}{res}{space 6}    0.008{col 35}{space 3}   -1.234{col 47}{space 3}    1.250{col 59}{space 5} 1.50
{col 1}{txt}         col_4_23{col 19}{c |}{res}{space 6}    0.325{col 35}{space 3}   -1.901{col 47}{space 3}    2.551{col 59}{space 5} 0.47
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}    0.164{col 35}{space 3}    0.010{col 47}{space 3}    0.317
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}2.09{txt}{col 50}Prob > |z| = {res}0.0369
{txt}Test of homogeneity: Q = chi2({res}11{txt}) = {res}18.01{txt}{col 52}Prob > Q = {res}0.0814
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient
{txt}{col 11}Std. Err.:  {res}stderr
{txt}{col 9}Study label:  {res}regression

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_our_noweights.png", replace  
{txt}(note: file Results/Figures_Electoral/forestplot_our_noweights.png not found)
(file Results/Figures_Electoral/forestplot_our_noweights.png written in PNG format)

{com}. 
. 
. * Replication period
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_term_2]
{txt}  4{com}.     local se = _se[top_prizes_gdp_term_2]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_89:col_4_89} are active now)
(results {stata estimates replay col_4_93:col_4_93} are active now)
(results {stata estimates replay col_4_96:col_4_96} are active now)
(results {stata estimates replay col_4_00:col_4_00} are active now)
(results {stata estimates replay col_4_04:col_4_04} are active now)
(results {stata estimates replay col_4_08:col_4_08} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient_pre
{res}{txt}
{com}. rename c2 stderr_pre
{res}{txt}
{com}. 
. gen regression_pre = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression_pre = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression_pre{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient_pre stderr_pre , studylabel(regression_pre)
{txt}(644 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}6
{col 8}{txt}Study label:  {res}regression_pre
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient_pre

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr_pre
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_pre
{txt}{col 11}Std. Err.:  {res}stderr_pre
{txt}{col 9}Study label:  {res}regression_pre

{txt}Meta-analysis summary{col 43}Number of studies = {res}     6
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 0.2154
{txt}{col 53}I2 (%) = {res}  80.76
{txt}{col 57}H2 = {res}   5.20

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_89{col 19}{c |}{res}{space 6}   -0.011{col 35}{space 3}   -0.243{col 47}{space 3}    0.222{col 59}{space 5}25.04
{col 1}{txt}         col_4_93{col 19}{c |}{res}{space 6}   -2.336{col 35}{space 3}   -4.125{col 47}{space 3}   -0.546{col 59}{space 5} 5.48
{col 1}{txt}         col_4_96{col 19}{c |}{res}{space 6}    1.260{col 35}{space 3}    0.372{col 47}{space 3}    2.148{col 59}{space 5}13.66
{col 1}{txt}         col_4_00{col 19}{c |}{res}{space 6}    0.732{col 35}{space 3}   -0.540{col 47}{space 3}    2.004{col 59}{space 5} 9.02
{col 1}{txt}         col_4_04{col 19}{c |}{res}{space 6}    0.190{col 35}{space 3}   -0.180{col 47}{space 3}    0.560{col 59}{space 5}22.88
{col 1}{txt}         col_4_08{col 19}{c |}{res}{space 6}    0.327{col 35}{space 3}    0.019{col 47}{space 3}    0.635{col 59}{space 5}23.93
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}    0.229{col 35}{space 3}   -0.241{col 47}{space 3}    0.699
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}0.96{txt}{col 50}Prob > |z| = {res}0.3390
{txt}Test of homogeneity: Q = chi2({res}5{txt}) = {res}17.36{txt}{col 52}Prob > Q = {res}0.0039
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_pre
{txt}{col 11}Std. Err.:  {res}stderr_pre
{txt}{col 9}Study label:  {res}regression_pre

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_pre_noweights.png", replace          
{txt}(note: file Results/Figures_Electoral/forestplot_pre_noweights.png not found)
(file Results/Figures_Electoral/forestplot_pre_noweights.png written in PNG format)

{com}. 
. 
. * Out-of-sample
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_term_2]
{txt}  4{com}.     local se = _se[top_prizes_gdp_term_2]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_11:col_4_11} are active now)
(results {stata estimates replay col_4_15:col_4_15} are active now)
(results {stata estimates replay col_4_16:col_4_16} are active now)
(results {stata estimates replay col_4_19_4:col_4_19_4} are active now)
(results {stata estimates replay col_4_19_11:col_4_19_11} are active now)
(results {stata estimates replay col_4_23:col_4_23} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient_post
{res}{txt}
{com}. rename c2 stderr_post
{res}{txt}
{com}. 
. gen regression_post = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression_post = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression_post{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
variable {bf}regression_post{sf} was {bf}{res}str8{sf}{txt} now {bf}{res}str10{sf}
{txt}(1 real change made)
variable {bf}regression_post{sf} was {bf}{res}str10{sf}{txt} now {bf}{res}str11{sf}
{txt}(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient_post stderr_post , studylabel(regression_post)
{txt}(644 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}6
{col 8}{txt}Study label:  {res}regression_post
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient_post

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr_post
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_post
{txt}{col 11}Std. Err.:  {res}stderr_post
{txt}{col 9}Study label:  {res}regression_post

{txt}Meta-analysis summary{col 43}Number of studies = {res}     6
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 0.0000
{txt}{col 53}I2 (%) = {res}   0.00
{txt}{col 57}H2 = {res}   1.00

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_11{col 19}{c |}{res}{space 6}   -0.147{col 35}{space 3}   -1.092{col 47}{space 3}    0.798{col 59}{space 5} 6.65
{col 1}{txt}         col_4_15{col 19}{c |}{res}{space 6}    0.036{col 35}{space 3}   -0.734{col 47}{space 3}    0.807{col 59}{space 5}10.00
{col 1}{txt}         col_4_16{col 19}{c |}{res}{space 6}    0.200{col 35}{space 3}   -0.103{col 47}{space 3}    0.503{col 59}{space 5}64.81
{col 1}{txt}       col_4_19_4{col 19}{c |}{res}{space 6}    0.174{col 35}{space 3}   -0.490{col 47}{space 3}    0.838{col 59}{space 5}13.47
{col 1}{txt}      col_4_19_11{col 19}{c |}{res}{space 6}    0.008{col 35}{space 3}   -1.234{col 47}{space 3}    1.250{col 59}{space 5} 3.85
{col 1}{txt}         col_4_23{col 19}{c |}{res}{space 6}    0.325{col 35}{space 3}   -1.901{col 47}{space 3}    2.551{col 59}{space 5} 1.20
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}    0.151{col 35}{space 3}   -0.093{col 47}{space 3}    0.395
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}1.21{txt}{col 50}Prob > |z| = {res}0.2246
{txt}Test of homogeneity: Q = chi2({res}5{txt}) = {res}0.65{txt}{col 52}Prob > Q = {res}0.9857
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_post
{txt}{col 11}Std. Err.:  {res}stderr_post
{txt}{col 9}Study label:  {res}regression_post

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_post_noweights.png", replace                 
{txt}(note: file Results/Figures_Electoral/forestplot_post_noweights.png not found)
(file Results/Figures_Electoral/forestplot_post_noweights.png written in PNG format)

{com}.                 
.                 
. restore
{txt}
{com}. 
. 
. 
. **----------------------------------------------------------------------------**
. *** OUR DATA (WITH POPULATION WEIGHTS)
. **----------------------------------------------------------------------------**
. preserve
{txt}
{com}. 
. 
. global controls_ours D_unemployment_rate_2 D_gdp_pc_2 D_cpi_2 D_housing_price_2
{txt}
{com}. replace D_housing_price_2=housing_price_growth_term_1 if D_housing_price_==.
{txt}(100 real changes made)

{com}. 
. 
. rename top_prizes_gdp_term_2 dummy
{res}{txt}
{com}. rename expenditure_gdp_term_2 dummy2
{res}{txt}
{com}. rename top_prizes_gdp_term_1 top_prizes_gdp_term_2
{res}{txt}
{com}. rename expenditure_gdp_term_1 expenditure_gdp_term_2
{res}{txt}
{com}. 
. eststo col_4_89: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==1989
{txt}(sum of wgt is 38,358,555)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}    14.76
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.4742
                                                {txt}Root MSE          =    {res} 1.9642

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2}  -.16293{col 36}{space 2} .2922334{col 47}{space 1}   -0.56{col 56}{space 3}0.580{col 64}{space 4}-.7522748{col 77}{space 3} .4264149
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} -1.98229{col 36}{space 2} 2.041815{col 47}{space 1}   -0.97{col 56}{space 3}0.337{col 64}{space 4}-6.100002{col 77}{space 3} 2.135422
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .1637675{col 36}{space 2} .1451158{col 47}{space 1}    1.13{col 56}{space 3}0.265{col 64}{space 4}-.1288864{col 77}{space 3} .4564213
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .1246353{col 36}{space 2} .0556915{col 47}{space 1}    2.24{col 56}{space 3}0.030{col 64}{space 4} .0123227{col 77}{space 3} .2369478
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}  -.51839{col 36}{space 2} .2123656{col 47}{space 1}   -2.44{col 56}{space 3}0.019{col 64}{space 4}-.9466661{col 77}{space 3}-.0901139
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0936143{col 36}{space 2} .0443446{col 47}{space 1}   -2.11{col 56}{space 3}0.041{col 64}{space 4}-.1830437{col 77}{space 3} -.004185
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}  8.50081{col 36}{space 2} 3.831681{col 47}{space 1}    2.22{col 56}{space 3}0.032{col 64}{space 4} .7734888{col 77}{space 3} 16.22813
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-4.0485859
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1989"

{txt}added macro:
           e(Election) : "{res:1989}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_93: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==1993
{txt}(sum of wgt is 38,745,485)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     3.29
                                                {txt}Prob > F          = {res}    0.0094
                                                {txt}R-squared         = {res}    0.3045
                                                {txt}Root MSE          =    {res} 2.4272

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2}-2.144092{col 36}{space 2} .9828277{col 47}{space 1}   -2.18{col 56}{space 3}0.035{col 64}{space 4}-4.126153{col 77}{space 3}-.1620306
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} 4.051247{col 36}{space 2} 1.923289{col 47}{space 1}    2.11{col 56}{space 3}0.041{col 64}{space 4} .1725651{col 77}{space 3} 7.929929
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.3934123{col 36}{space 2} .1373372{col 47}{space 1}   -2.86{col 56}{space 3}0.006{col 64}{space 4}-.6703793{col 77}{space 3}-.1164454
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .1079193{col 36}{space 2} .0650808{col 47}{space 1}    1.66{col 56}{space 3}0.105{col 64}{space 4}-.0233287{col 77}{space 3} .2391673
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .0062969{col 36}{space 2} .0964808{col 47}{space 1}    0.07{col 56}{space 3}0.948{col 64}{space 4}-.1882751{col 77}{space 3} .2008689
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .1874731{col 36}{space 2} .1161139{col 47}{space 1}    1.61{col 56}{space 3}0.114{col 64}{space 4} -.046693{col 77}{space 3} .4216392
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-3.185109{col 36}{space 2} 3.015105{col 47}{space 1}   -1.06{col 56}{space 3}0.297{col 64}{space 4}-9.265647{col 77}{space 3} 2.895428
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-.81496548
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1993"

{txt}added macro:
           e(Election) : "{res:1993}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_96: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==1996
{txt}(sum of wgt is 40,095,757)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     4.36
                                                {txt}Prob > F          = {res}    0.0016
                                                {txt}R-squared         = {res}    0.3919
                                                {txt}Root MSE          =    {res} 2.6918

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} 1.953324{col 36}{space 2}  .844917{col 47}{space 1}    2.31{col 56}{space 3}0.026{col 64}{space 4} .2493861{col 77}{space 3} 3.657261
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-.4416577{col 36}{space 2} 1.856091{col 47}{space 1}   -0.24{col 56}{space 3}0.813{col 64}{space 4}-4.184822{col 77}{space 3} 3.301506
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0911921{col 36}{space 2} .1084527{col 47}{space 1}    0.84{col 56}{space 3}0.405{col 64}{space 4}-.1275235{col 77}{space 3} .3099078
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .1336665{col 36}{space 2} .0927679{col 47}{space 1}    1.44{col 56}{space 3}0.157{col 64}{space 4}-.0534178{col 77}{space 3} .3207507
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .0972878{col 36}{space 2} .3713408{col 47}{space 1}    0.26{col 56}{space 3}0.795{col 64}{space 4}-.6515924{col 77}{space 3} .8461679
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}  .496837{col 36}{space 2} .1132652{col 47}{space 1}    4.39{col 56}{space 3}0.000{col 64}{space 4} .2684159{col 77}{space 3} .7252581
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-1.842432{col 36}{space 2} 5.830832{col 47}{space 1}   -0.32{col 56}{space 3}0.754{col 64}{space 4}-13.60143{col 77}{space 3} 9.916561
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-1.1695254
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1996"

{txt}added macro:
           e(Election) : "{res:1996}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_00: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==2000
{txt}(sum of wgt is 39,720,426)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     0.91
                                                {txt}Prob > F          = {res}    0.4976
                                                {txt}R-squared         = {res}    0.1408
                                                {txt}Root MSE          =    {res} 2.4979

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .9213179{col 36}{space 2} .8331761{col 47}{space 1}    1.11{col 56}{space 3}0.275{col 64}{space 4}-.7589419{col 77}{space 3} 2.601578
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-1.417653{col 36}{space 2} 1.879059{col 47}{space 1}   -0.75{col 56}{space 3}0.455{col 64}{space 4}-5.207137{col 77}{space 3} 2.371831
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.0294291{col 36}{space 2} .1466521{col 47}{space 1}   -0.20{col 56}{space 3}0.842{col 64}{space 4}-.3251813{col 77}{space 3} .2663231
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0042993{col 36}{space 2} .0277728{col 47}{space 1}    0.15{col 56}{space 3}0.878{col 64}{space 4}-.0517098{col 77}{space 3} .0603084
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}  .373293{col 36}{space 2}  .360401{col 47}{space 1}    1.04{col 56}{space 3}0.306{col 64}{space 4}-.3535248{col 77}{space 3} 1.100111
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0238461{col 36}{space 2} .0381855{col 47}{space 1}    0.62{col 56}{space 3}0.536{col 64}{space 4}-.0531623{col 77}{space 3} .1008546
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 2.331337{col 36}{space 2} 3.475549{col 47}{space 1}    0.67{col 56}{space 3}0.506{col 64}{space 4}-4.677776{col 77}{space 3}  9.34045
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}5.3671864
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2000"

{txt}added macro:
           e(Election) : "{res:2000}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_04: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==2004
{txt}(sum of wgt is 42,573,670)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     1.78
                                                {txt}Prob > F          = {res}    0.1263
                                                {txt}R-squared         = {res}    0.1908
                                                {txt}Root MSE          =    {res} 2.1738

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .6610113{col 36}{space 2} .6274529{col 47}{space 1}    1.05{col 56}{space 3}0.298{col 64}{space 4} -.604368{col 77}{space 3} 1.926391
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} 1.728775{col 36}{space 2} 1.032281{col 47}{space 1}    1.67{col 56}{space 3}0.101{col 64}{space 4}-.3530187{col 77}{space 3} 3.810569
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.0606272{col 36}{space 2} .1056168{col 47}{space 1}   -0.57{col 56}{space 3}0.569{col 64}{space 4}-.2736239{col 77}{space 3} .1523694
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0287794{col 36}{space 2} .0499237{col 47}{space 1}    0.58{col 56}{space 3}0.567{col 64}{space 4}-.0719013{col 77}{space 3}   .12946
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.1811244{col 36}{space 2} .3209121{col 47}{space 1}   -0.56{col 56}{space 3}0.575{col 64}{space 4}-.8283053{col 77}{space 3} .4660566
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0036073{col 36}{space 2} .0156278{col 47}{space 1}   -0.23{col 56}{space 3}0.819{col 64}{space 4}-.0351236{col 77}{space 3} .0279091
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-6.517608{col 36}{space 2} 4.146292{col 47}{space 1}   -1.57{col 56}{space 3}0.123{col 64}{space 4} -14.8794{col 77}{space 3} 1.844186
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-6.6068785
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2004"

{txt}added macro:
           e(Election) : "{res:2004}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_08: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==2008
{txt}(sum of wgt is 45,054,694)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.45
                                                {txt}Prob > F          = {res}    0.0397
                                                {txt}R-squared         = {res}    0.1593
                                                {txt}Root MSE          =    {res} 4.4839

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2}  .705091{col 36}{space 2} .4593085{col 47}{space 1}    1.54{col 56}{space 3}0.132{col 64}{space 4}-.2211929{col 77}{space 3} 1.631375
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-2.943513{col 36}{space 2} 2.212368{col 47}{space 1}   -1.33{col 56}{space 3}0.190{col 64}{space 4}-7.405178{col 77}{space 3} 1.518152
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.2697012{col 36}{space 2} .1820874{col 47}{space 1}   -1.48{col 56}{space 3}0.146{col 64}{space 4}-.6369155{col 77}{space 3} .0975131
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.0526131{col 36}{space 2} .1462497{col 47}{space 1}   -0.36{col 56}{space 3}0.721{col 64}{space 4}-.3475537{col 77}{space 3} .2423275
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .8110808{col 36}{space 2} .7314839{col 47}{space 1}    1.11{col 56}{space 3}0.274{col 64}{space 4} -.664097{col 77}{space 3} 2.286259
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}  .026841{col 36}{space 2}  .134532{col 47}{space 1}    0.20{col 56}{space 3}0.843{col 64}{space 4}-.2444687{col 77}{space 3} .2981507
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-5.295269{col 36}{space 2}   12.696{col 47}{space 1}   -0.42{col 56}{space 3}0.679{col 64}{space 4}-30.89918{col 77}{space 3} 20.30865
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}1.3883849
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2008"

{txt}added macro:
           e(Election) : "{res:2008}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. 
. rename expenditure_gdp_term_2 expenditure_gdp_term_1 
{res}{txt}
{com}. rename top_prizes_gdp_term_2 top_prizes_gdp_term_1 
{res}{txt}
{com}. rename dummy2 expenditure_gdp_term_2 
{res}{txt}
{com}. rename dummy top_prizes_gdp_term_2 
{res}{txt}
{com}. 
. 
. 
. eststo col_4_11: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==2011
{txt}(sum of wgt is 46,864,418)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.92
                                                {txt}Prob > F          = {res}    0.0176
                                                {txt}R-squared         = {res}    0.2808
                                                {txt}Root MSE          =    {res} 2.0252

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2}-.4560309{col 36}{space 2} 1.510134{col 47}{space 1}   -0.30{col 56}{space 3}0.764{col 64}{space 4}-3.501507{col 77}{space 3} 2.589445
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} 3.425904{col 36}{space 2} 1.514331{col 47}{space 1}    2.26{col 56}{space 3}0.029{col 64}{space 4} .3719637{col 77}{space 3} 6.479844
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0598572{col 36}{space 2} .1328356{col 47}{space 1}    0.45{col 56}{space 3}0.655{col 64}{space 4}-.2080313{col 77}{space 3} .3277457
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.1213629{col 36}{space 2} .0993221{col 47}{space 1}   -1.22{col 56}{space 3}0.228{col 64}{space 4}-.3216649{col 77}{space 3} .0789392
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.7755022{col 36}{space 2} .4184312{col 47}{space 1}   -1.85{col 56}{space 3}0.071{col 64}{space 4}-1.619349{col 77}{space 3} .0683447
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0962138{col 36}{space 2} .0493658{col 47}{space 1}    1.95{col 56}{space 3}0.058{col 64}{space 4}-.0033417{col 77}{space 3} .1957694
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-12.33182{col 36}{space 2}  3.24825{col 47}{space 1}   -3.80{col 56}{space 3}0.000{col 64}{space 4}-18.88254{col 77}{space 3}-5.781103
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-15.269305
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2011"

{txt}added macro:
           e(Election) : "{res:2011}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_15: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==2015
{txt}(sum of wgt is 46,607,325)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     5.83
                                                {txt}Prob > F          = {res}    0.0002
                                                {txt}R-squared         = {res}    0.3842
                                                {txt}Root MSE          =    {res} 4.1362

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2}-.4949566{col 36}{space 2} 1.184843{col 47}{space 1}   -0.42{col 56}{space 3}0.678{col 64}{space 4} -2.88442{col 77}{space 3} 1.894507
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-1.837576{col 36}{space 2} 2.886831{col 47}{space 1}   -0.64{col 56}{space 3}0.528{col 64}{space 4}-7.659425{col 77}{space 3} 3.984273
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .9673051{col 36}{space 2}  .295733{col 47}{space 1}    3.27{col 56}{space 3}0.002{col 64}{space 4} .3709026{col 77}{space 3} 1.563708
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0491909{col 36}{space 2} .3006439{col 47}{space 1}    0.16{col 56}{space 3}0.871{col 64}{space 4}-.5571153{col 77}{space 3} .6554972
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} 2.756001{col 36}{space 2} .7262998{col 47}{space 1}    3.79{col 56}{space 3}0.000{col 64}{space 4} 1.291277{col 77}{space 3} 4.220724
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0142322{col 36}{space 2} .1303488{col 47}{space 1}   -0.11{col 56}{space 3}0.914{col 64}{space 4}-.2771057{col 77}{space 3} .2486413
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-17.67722{col 36}{space 2} 3.303141{col 47}{space 1}   -5.35{col 56}{space 3}0.000{col 64}{space 4}-24.33864{col 77}{space 3} -11.0158
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-15.434881
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2015"

{txt}added macro:
           e(Election) : "{res:2015}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_16: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==2016
{txt}(sum of wgt is 46,454,535)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.44
                                                {txt}Prob > F          = {res}    0.0402
                                                {txt}R-squared         = {res}    0.3128
                                                {txt}Root MSE          =    {res} 1.1388

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .3929964{col 36}{space 2} .1935078{col 47}{space 1}    2.03{col 56}{space 3}0.048{col 64}{space 4} .0027507{col 77}{space 3} .7832421
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} 2.644198{col 36}{space 2} 1.836454{col 47}{space 1}    1.44{col 56}{space 3}0.157{col 64}{space 4}-1.059363{col 77}{space 3}  6.34776
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.1840015{col 36}{space 2} .1305776{col 47}{space 1}   -1.41{col 56}{space 3}0.166{col 64}{space 4}-.4473364{col 77}{space 3} .0793335
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0133318{col 36}{space 2} .0995174{col 47}{space 1}    0.13{col 56}{space 3}0.894{col 64}{space 4}-.1873641{col 77}{space 3} .2140277
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-2.791874{col 36}{space 2}  .999307{col 47}{space 1}   -2.79{col 56}{space 3}0.008{col 64}{space 4}-4.807169{col 77}{space 3}-.7765795
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0116841{col 36}{space 2} .0566142{col 47}{space 1}    0.21{col 56}{space 3}0.837{col 64}{space 4}-.1024895{col 77}{space 3} .1258576
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 7.326666{col 36}{space 2} 1.670614{col 47}{space 1}    4.39{col 56}{space 3}0.000{col 64}{space 4} 3.957551{col 77}{space 3} 10.69578
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}4.1184794
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2016"

{txt}added macro:
           e(Election) : "{res:2016}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_19_4: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==2019 & month==4
{txt}(sum of wgt is 46,551,452)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     7.78
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.3429
                                                {txt}Root MSE          =    {res} 1.8254

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} .1234468{col 36}{space 2} .4541531{col 47}{space 1}    0.27{col 56}{space 3}0.787{col 64}{space 4}-.7924403{col 77}{space 3} 1.039334
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-.1827027{col 36}{space 2}  3.16908{col 47}{space 1}   -0.06{col 56}{space 3}0.954{col 64}{space 4}-6.573761{col 77}{space 3} 6.208356
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .4040085{col 36}{space 2} .1148236{col 47}{space 1}    3.52{col 56}{space 3}0.001{col 64}{space 4} .1724447{col 77}{space 3} .6355723
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0752592{col 36}{space 2} .1169717{col 47}{space 1}    0.64{col 56}{space 3}0.523{col 64}{space 4}-.1606367{col 77}{space 3} .3111552
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} 1.406636{col 36}{space 2} .5836791{col 47}{space 1}    2.41{col 56}{space 3}0.020{col 64}{space 4} .2295348{col 77}{space 3} 2.583737
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0520667{col 36}{space 2} .0557079{col 47}{space 1}    0.93{col 56}{space 3}0.355{col 64}{space 4} -.060279{col 77}{space 3} .1644123
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 2.576391{col 36}{space 2}  2.43926{col 47}{space 1}    1.06{col 56}{space 3}0.297{col 64}{space 4}-2.342845{col 77}{space 3} 7.495627
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}6.0366904
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2019 (4)"

{txt}added macro:
           e(Election) : "{res:2019 (4)}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_19_11: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==2019 & month==11
{txt}(sum of wgt is 46,551,452)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     3.90
                                                {txt}Prob > F          = {res}    0.0034
                                                {txt}R-squared         = {res}    0.3427
                                                {txt}Root MSE          =    {res} 1.0977

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2}-.0419725{col 36}{space 2} .4469507{col 47}{space 1}   -0.09{col 56}{space 3}0.926{col 64}{space 4}-.9433345{col 77}{space 3} .8593896
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2} 7.126828{col 36}{space 2} 2.333507{col 47}{space 1}    3.05{col 56}{space 3}0.004{col 64}{space 4} 2.420863{col 77}{space 3} 11.83279
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0036182{col 36}{space 2} .0678088{col 47}{space 1}    0.05{col 56}{space 3}0.958{col 64}{space 4}-.1331313{col 77}{space 3} .1403677
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}  .079579{col 36}{space 2}  .056691{col 47}{space 1}    1.40{col 56}{space 3}0.168{col 64}{space 4}-.0347493{col 77}{space 3} .1939073
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.4348949{col 36}{space 2} .3969542{col 47}{space 1}   -1.10{col 56}{space 3}0.279{col 64}{space 4}-1.235429{col 77}{space 3} .3656396
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0183566{col 36}{space 2} .0377516{col 47}{space 1}   -0.49{col 56}{space 3}0.629{col 64}{space 4}-.0944899{col 77}{space 3} .0577767
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-1.281297{col 36}{space 2} 1.176429{col 47}{space 1}   -1.09{col 56}{space 3}0.282{col 64}{space 4}-3.653793{col 77}{space 3} 1.091199
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-.6449239
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2019 (4)"

{txt}added macro:
           e(Election) : "{res:2019 (4)}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_23: reg var_votes_inc_ours top_prizes_gdp_term_2 expenditure_gdp_term_2 $controls_ours [pw=population], robust , if year==2023
{txt}(sum of wgt is 47,307,133)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.74
                                                {txt}Prob > F          = {res}    0.0239
                                                {txt}R-squared         = {res}    0.3861
                                                {txt}Root MSE          =    {res} 4.1765

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_term_2 {c |}{col 24}{res}{space 2} 1.210321{col 36}{space 2} 1.431028{col 47}{space 1}    0.85{col 56}{space 3}0.402{col 64}{space 4}-1.675623{col 77}{space 3} 4.096265
{txt}expenditure_gdp_term_2 {c |}{col 24}{res}{space 2}-4.279652{col 36}{space 2} 2.430529{col 47}{space 1}   -1.76{col 56}{space 3}0.085{col 64}{space 4}-9.181281{col 77}{space 3} .6219776
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.0936784{col 36}{space 2} .3126093{col 47}{space 1}   -0.30{col 56}{space 3}0.766{col 64}{space 4} -.724115{col 77}{space 3} .5367583
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} -.430506{col 36}{space 2} .3008585{col 47}{space 1}   -1.43{col 56}{space 3}0.160{col 64}{space 4}-1.037245{col 77}{space 3} .1762331
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-1.240849{col 36}{space 2}  1.13947{col 47}{space 1}   -1.09{col 56}{space 3}0.282{col 64}{space 4}-3.538809{col 77}{space 3} 1.057112
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.2120094{col 36}{space 2}  .149087{col 47}{space 1}   -1.42{col 56}{space 3}0.162{col 64}{space 4} -.512672{col 77}{space 3} .0886532
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 23.32722{col 36}{space 2} 15.93468{col 47}{space 1}    1.46{col 56}{space 3}0.150{col 64}{space 4} -8.80813{col 77}{space 3} 55.46258
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}3.7700635
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2023"

{txt}added macro:
           e(Election) : "{res:2023}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_all: reg var_votes_inc_ours top_prizes_gdp_term_2 c.expenditure_gdp_term_2##i.year $controls_ours i.province_num [pw=population], robust
{txt}(sum of wgt is 524,884,902)

Linear regression                               Number of obs     = {res}       600
                                                {txt}F(75, 524)        =  {res}    28.94
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8417
                                                {txt}Root MSE          =    {res} 3.3277

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}           var_votes_inc_ours{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}top_prizes_gdp_term_2 {c |}{col 31}{res}{space 2} .4531574{col 43}{space 2} .2674871{col 54}{space 1}    1.69{col 63}{space 3}0.091{col 71}{space 4}-.0723214{col 84}{space 3} .9786361
{txt}{space 7}expenditure_gdp_term_2 {c |}{col 31}{res}{space 2}-5.817905{col 43}{space 2} 2.491894{col 54}{space 1}   -2.33{col 63}{space 3}0.020{col 71}{space 4}-10.71323{col 84}{space 3}-.9225745
{txt}{space 29} {c |}
{space 25}year {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} .4119254{col 43}{space 2}  3.06732{col 54}{space 1}    0.13{col 63}{space 3}0.893{col 71}{space 4} -5.61383{col 84}{space 3} 6.437681
{txt}{space 24}1996  {c |}{col 31}{res}{space 2}-1.483183{col 43}{space 2} 2.310814{col 54}{space 1}   -0.64{col 63}{space 3}0.521{col 71}{space 4}-6.022781{col 84}{space 3} 3.056415
{txt}{space 24}2000  {c |}{col 31}{res}{space 2} 5.015095{col 43}{space 2} 2.889336{col 54}{space 1}    1.74{col 63}{space 3}0.083{col 71}{space 4}-.6610091{col 84}{space 3}  10.6912
{txt}{space 24}2004  {c |}{col 31}{res}{space 2}-10.11071{col 43}{space 2} 2.577113{col 54}{space 1}   -3.92{col 63}{space 3}0.000{col 71}{space 4}-15.17345{col 84}{space 3}-5.047968
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} 4.049055{col 43}{space 2} 3.053825{col 54}{space 1}    1.33{col 63}{space 3}0.185{col 71}{space 4}-1.950189{col 84}{space 3}  10.0483
{txt}{space 24}2011  {c |}{col 31}{res}{space 2}-18.32162{col 43}{space 2} 3.381537{col 54}{space 1}   -5.42{col 63}{space 3}0.000{col 71}{space 4}-24.96466{col 84}{space 3}-11.67859
{txt}{space 24}2015  {c |}{col 31}{res}{space 2}-16.22216{col 43}{space 2} 4.383873{col 54}{space 1}   -3.70{col 63}{space 3}0.000{col 71}{space 4}-24.83429{col 84}{space 3}-7.610039
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} .2281618{col 43}{space 2} 3.671536{col 54}{space 1}    0.06{col 63}{space 3}0.950{col 71}{space 4}-6.984576{col 84}{space 3}   7.4409
{txt}{space 24}2019  {c |}{col 31}{res}{space 2}-1.329348{col 43}{space 2} 4.078463{col 54}{space 1}   -0.33{col 63}{space 3}0.745{col 71}{space 4}-9.341494{col 84}{space 3} 6.682798
{txt}{space 24}2023  {c |}{col 31}{res}{space 2} 9.294892{col 43}{space 2} 3.858969{col 54}{space 1}    2.41{col 63}{space 3}0.016{col 71}{space 4} 1.713941{col 84}{space 3} 16.87584
{txt}{space 29} {c |}
year#c.expenditure_gdp_term_2 {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} 6.550624{col 43}{space 2} 2.941664{col 54}{space 1}    2.23{col 63}{space 3}0.026{col 71}{space 4} .7717205{col 84}{space 3} 12.32953
{txt}{space 24}1996  {c |}{col 31}{res}{space 2} 5.136536{col 43}{space 2} 2.666878{col 54}{space 1}    1.93{col 63}{space 3}0.055{col 71}{space 4}-.1025499{col 84}{space 3} 10.37562
{txt}{space 24}2000  {c |}{col 31}{res}{space 2} 3.966062{col 43}{space 2} 2.590188{col 54}{space 1}    1.53{col 63}{space 3}0.126{col 71}{space 4}-1.122366{col 84}{space 3} 9.054489
{txt}{space 24}2004  {c |}{col 31}{res}{space 2} 7.125339{col 43}{space 2} 2.321003{col 54}{space 1}    3.07{col 63}{space 3}0.002{col 71}{space 4} 2.565726{col 84}{space 3} 11.68495
{txt}{space 24}2008  {c |}{col 31}{res}{space 2}  2.09946{col 43}{space 2} 2.731095{col 54}{space 1}    0.77{col 63}{space 3}0.442{col 71}{space 4} -3.26578{col 84}{space 3}   7.4647
{txt}{space 24}2011  {c |}{col 31}{res}{space 2} 7.743751{col 43}{space 2} 2.918109{col 54}{space 1}    2.65{col 63}{space 3}0.008{col 71}{space 4} 2.011122{col 84}{space 3} 13.47638
{txt}{space 24}2015  {c |}{col 31}{res}{space 2} 3.463451{col 43}{space 2} 3.292382{col 54}{space 1}    1.05{col 63}{space 3}0.293{col 71}{space 4}-3.004438{col 84}{space 3}  9.93134
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} 7.938807{col 43}{space 2} 6.553035{col 54}{space 1}    1.21{col 63}{space 3}0.226{col 71}{space 4}-4.934641{col 84}{space 3} 20.81225
{txt}{space 24}2019  {c |}{col 31}{res}{space 2} 8.673554{col 43}{space 2} 9.712344{col 54}{space 1}    0.89{col 63}{space 3}0.372{col 71}{space 4}-10.40636{col 84}{space 3} 27.75347
{txt}{space 24}2023  {c |}{col 31}{res}{space 2}-1.186588{col 43}{space 2} 3.641974{col 54}{space 1}   -0.33{col 63}{space 3}0.745{col 71}{space 4}-8.341252{col 84}{space 3} 5.968076
{txt}{space 29} {c |}
{space 8}D_unemployment_rate_2 {c |}{col 31}{res}{space 2}-.0263886{col 43}{space 2} .0602144{col 54}{space 1}   -0.44{col 63}{space 3}0.661{col 71}{space 4}-.1446799{col 84}{space 3} .0919027
{txt}{space 19}D_gdp_pc_2 {c |}{col 31}{res}{space 2} .0114177{col 43}{space 2} .0241038{col 54}{space 1}    0.47{col 63}{space 3}0.636{col 71}{space 4}-.0359342{col 84}{space 3} .0587695
{txt}{space 22}D_cpi_2 {c |}{col 31}{res}{space 2}-.2153848{col 43}{space 2} .1802215{col 54}{space 1}   -1.20{col 63}{space 3}0.233{col 71}{space 4}-.5694303{col 84}{space 3} .1386607
{txt}{space 12}D_housing_price_2 {c |}{col 31}{res}{space 2} .0196482{col 43}{space 2} .0214254{col 54}{space 1}    0.92{col 63}{space 3}0.360{col 71}{space 4} -.022442{col 84}{space 3} .0617384
{txt}{space 29} {c |}
{space 17}province_num {c |}
{space 23}alava  {c |}{col 31}{res}{space 2} .5938795{col 43}{space 2} 1.723696{col 54}{space 1}    0.34{col 63}{space 3}0.731{col 71}{space 4}-2.792324{col 84}{space 3} 3.980083
{txt}{space 20}albacete  {c |}{col 31}{res}{space 2}-.2847114{col 43}{space 2} 1.017126{col 54}{space 1}   -0.28{col 63}{space 3}0.780{col 71}{space 4}-2.282857{col 84}{space 3} 1.713434
{txt}{space 20}alicante  {c |}{col 31}{res}{space 2}-.4007223{col 43}{space 2} 1.288314{col 54}{space 1}   -0.31{col 63}{space 3}0.756{col 71}{space 4}-2.931617{col 84}{space 3} 2.130173
{txt}{space 21}almeria  {c |}{col 31}{res}{space 2}-1.451139{col 43}{space 2} 1.339142{col 54}{space 1}   -1.08{col 63}{space 3}0.279{col 71}{space 4}-4.081885{col 84}{space 3} 1.179608
{txt}{space 20}asturias  {c |}{col 31}{res}{space 2} 1.373757{col 43}{space 2} 1.464918{col 54}{space 1}    0.94{col 63}{space 3}0.349{col 71}{space 4}-1.504076{col 84}{space 3}  4.25159
{txt}{space 23}avila  {c |}{col 31}{res}{space 2} 1.918681{col 43}{space 2} 1.257307{col 54}{space 1}    1.53{col 63}{space 3}0.128{col 71}{space 4}-.5512997{col 84}{space 3} 4.388662
{txt}{space 21}badajoz  {c |}{col 31}{res}{space 2}-.7682255{col 43}{space 2} 1.071371{col 54}{space 1}   -0.72{col 63}{space 3}0.474{col 71}{space 4}-2.872935{col 84}{space 3} 1.336484
{txt}{space 19}barcelona  {c |}{col 31}{res}{space 2} 1.133924{col 43}{space 2} 1.498417{col 54}{space 1}    0.76{col 63}{space 3}0.450{col 71}{space 4}-1.809718{col 84}{space 3} 4.077567
{txt}{space 22}burgos  {c |}{col 31}{res}{space 2} .6429675{col 43}{space 2} 1.204188{col 54}{space 1}    0.53{col 63}{space 3}0.594{col 71}{space 4}-1.722661{col 84}{space 3} 3.008596
{txt}{space 21}caceres  {c |}{col 31}{res}{space 2} .0192414{col 43}{space 2} 1.013362{col 54}{space 1}    0.02{col 63}{space 3}0.985{col 71}{space 4} -1.97151{col 84}{space 3} 2.009993
{txt}{space 23}cadiz  {c |}{col 31}{res}{space 2}-2.590161{col 43}{space 2} 1.296071{col 54}{space 1}   -2.00{col 63}{space 3}0.046{col 71}{space 4}-5.136294{col 84}{space 3}-.0440278
{txt}{space 19}cantabria  {c |}{col 31}{res}{space 2} -.019852{col 43}{space 2} 1.302791{col 54}{space 1}   -0.02{col 63}{space 3}0.988{col 71}{space 4}-2.579187{col 84}{space 3} 2.539483
{txt}{space 19}castellon  {c |}{col 31}{res}{space 2}-.4482611{col 43}{space 2} 1.199324{col 54}{space 1}   -0.37{col 63}{space 3}0.709{col 71}{space 4}-2.804334{col 84}{space 3} 1.907812
{txt}{space 17}ciudad real  {c |}{col 31}{res}{space 2} .0890477{col 43}{space 2} 1.227393{col 54}{space 1}    0.07{col 63}{space 3}0.942{col 71}{space 4}-2.322168{col 84}{space 3} 2.500263
{txt}{space 21}cordoba  {c |}{col 31}{res}{space 2}-.7404258{col 43}{space 2} 1.058055{col 54}{space 1}   -0.70{col 63}{space 3}0.484{col 71}{space 4}-2.818977{col 84}{space 3} 1.338125
{txt}{space 22}cuenca  {c |}{col 31}{res}{space 2} .9815727{col 43}{space 2} 1.339172{col 54}{space 1}    0.73{col 63}{space 3}0.464{col 71}{space 4}-1.649232{col 84}{space 3} 3.612377
{txt}{space 20}gipuzkoa  {c |}{col 31}{res}{space 2} 1.519324{col 43}{space 2} 1.871675{col 54}{space 1}    0.81{col 63}{space 3}0.417{col 71}{space 4}-2.157583{col 84}{space 3} 5.196232
{txt}{space 22}girona  {c |}{col 31}{res}{space 2} 1.838027{col 43}{space 2} 1.765353{col 54}{space 1}    1.04{col 63}{space 3}0.298{col 71}{space 4}-1.630011{col 84}{space 3} 5.306066
{txt}{space 21}granada  {c |}{col 31}{res}{space 2}-.8807344{col 43}{space 2} 1.033317{col 54}{space 1}   -0.85{col 63}{space 3}0.394{col 71}{space 4}-2.910687{col 84}{space 3} 1.149219
{txt}{space 17}guadalajara  {c |}{col 31}{res}{space 2}-.5589468{col 43}{space 2} 1.145362{col 54}{space 1}   -0.49{col 63}{space 3}0.626{col 71}{space 4}-2.809013{col 84}{space 3} 1.691119
{txt}{space 22}huelva  {c |}{col 31}{res}{space 2}-2.220778{col 43}{space 2} 1.451294{col 54}{space 1}   -1.53{col 63}{space 3}0.127{col 71}{space 4}-5.071847{col 84}{space 3} .6302908
{txt}{space 22}huesca  {c |}{col 31}{res}{space 2}-.2960785{col 43}{space 2} 1.258103{col 54}{space 1}   -0.24{col 63}{space 3}0.814{col 71}{space 4}-2.767625{col 84}{space 3} 2.175468
{txt}{space 14}islas baleares  {c |}{col 31}{res}{space 2}-.4837846{col 43}{space 2} 1.504172{col 54}{space 1}   -0.32{col 63}{space 3}0.748{col 71}{space 4}-3.438733{col 84}{space 3} 2.471164
{txt}{space 24}jaen  {c |}{col 31}{res}{space 2}-.9025851{col 43}{space 2} 1.071592{col 54}{space 1}   -0.84{col 63}{space 3}0.400{col 71}{space 4}-3.007729{col 84}{space 3} 1.202559
{txt}{space 20}la rioja  {c |}{col 31}{res}{space 2} .6912229{col 43}{space 2}  .983333{col 54}{space 1}    0.70{col 63}{space 3}0.482{col 71}{space 4}-1.240536{col 84}{space 3} 2.622982
{txt}{space 18}las palmas  {c |}{col 31}{res}{space 2}-.6957424{col 43}{space 2} 1.618883{col 54}{space 1}   -0.43{col 63}{space 3}0.668{col 71}{space 4} -3.87604{col 84}{space 3} 2.484555
{txt}{space 24}leon  {c |}{col 31}{res}{space 2} .0625422{col 43}{space 2} 1.186795{col 54}{space 1}    0.05{col 63}{space 3}0.958{col 71}{space 4}-2.268919{col 84}{space 3} 2.394003
{txt}{space 22}lleida  {c |}{col 31}{res}{space 2} 2.687045{col 43}{space 2} 2.225663{col 54}{space 1}    1.21{col 63}{space 3}0.228{col 71}{space 4}-1.685273{col 84}{space 3} 7.059363
{txt}{space 24}lugo  {c |}{col 31}{res}{space 2} .9563605{col 43}{space 2} 1.267247{col 54}{space 1}    0.75{col 63}{space 3}0.451{col 71}{space 4}-1.533148{col 84}{space 3} 3.445869
{txt}{space 22}madrid  {c |}{col 31}{res}{space 2}-1.281171{col 43}{space 2} 1.319748{col 54}{space 1}   -0.97{col 63}{space 3}0.332{col 71}{space 4}-3.873818{col 84}{space 3} 1.311476
{txt}{space 22}malaga  {c |}{col 31}{res}{space 2}-2.251608{col 43}{space 2} 1.156518{col 54}{space 1}   -1.95{col 63}{space 3}0.052{col 71}{space 4} -4.52359{col 84}{space 3}  .020373
{txt}{space 22}murcia  {c |}{col 31}{res}{space 2}-.6230213{col 43}{space 2} 1.501359{col 54}{space 1}   -0.41{col 63}{space 3}0.678{col 71}{space 4}-3.572442{col 84}{space 3}   2.3264
{txt}{space 21}navarra  {c |}{col 31}{res}{space 2} .5342722{col 43}{space 2} 1.678537{col 54}{space 1}    0.32{col 63}{space 3}0.750{col 71}{space 4}-2.763216{col 84}{space 3}  3.83176
{txt}{space 21}ourense  {c |}{col 31}{res}{space 2} 2.237824{col 43}{space 2} 1.502161{col 54}{space 1}    1.49{col 63}{space 3}0.137{col 71}{space 4}-.7131737{col 84}{space 3} 5.188822
{txt}{space 20}palencia  {c |}{col 31}{res}{space 2} 1.001273{col 43}{space 2} 1.137796{col 54}{space 1}    0.88{col 63}{space 3}0.379{col 71}{space 4}-1.233928{col 84}{space 3} 3.236474
{txt}{space 18}pontevedra  {c |}{col 31}{res}{space 2} .5076269{col 43}{space 2} 1.242412{col 54}{space 1}    0.41{col 63}{space 3}0.683{col 71}{space 4}-1.933093{col 84}{space 3} 2.948347
{txt}{space 19}salamanca  {c |}{col 31}{res}{space 2}  .144605{col 43}{space 2} 1.026942{col 54}{space 1}    0.14{col 63}{space 3}0.888{col 71}{space 4}-1.872825{col 84}{space 3} 2.162035
{txt}{space 6}santa cruz de tenerife  {c |}{col 31}{res}{space 2} .0646689{col 43}{space 2} 1.137278{col 54}{space 1}    0.06{col 63}{space 3}0.955{col 71}{space 4}-2.169515{col 84}{space 3} 2.298853
{txt}{space 21}segovia  {c |}{col 31}{res}{space 2} .8818123{col 43}{space 2} 1.581924{col 54}{space 1}    0.56{col 63}{space 3}0.577{col 71}{space 4}-2.225881{col 84}{space 3} 3.989505
{txt}{space 21}sevilla  {c |}{col 31}{res}{space 2} -1.56283{col 43}{space 2} 1.266071{col 54}{space 1}   -1.23{col 63}{space 3}0.218{col 71}{space 4}-4.050028{col 84}{space 3} .9243679
{txt}{space 23}soria  {c |}{col 31}{res}{space 2} .5582848{col 43}{space 2} 2.793768{col 54}{space 1}    0.20{col 63}{space 3}0.842{col 71}{space 4}-4.930076{col 84}{space 3} 6.046646
{txt}{space 19}tarragona  {c |}{col 31}{res}{space 2} .8142389{col 43}{space 2} 1.701402{col 54}{space 1}    0.48{col 63}{space 3}0.632{col 71}{space 4}-2.528168{col 84}{space 3} 4.156645
{txt}{space 22}teruel  {c |}{col 31}{res}{space 2} .0353695{col 43}{space 2} 1.556026{col 54}{space 1}    0.02{col 63}{space 3}0.982{col 71}{space 4}-3.021446{col 84}{space 3} 3.092185
{txt}{space 22}toledo  {c |}{col 31}{res}{space 2}-.5280355{col 43}{space 2} 1.087657{col 54}{space 1}   -0.49{col 63}{space 3}0.628{col 71}{space 4}-2.664739{col 84}{space 3} 1.608668
{txt}{space 20}valencia  {c |}{col 31}{res}{space 2}-.2816716{col 43}{space 2} 1.292746{col 54}{space 1}   -0.22{col 63}{space 3}0.828{col 71}{space 4}-2.821273{col 84}{space 3}  2.25793
{txt}{space 18}valladolid  {c |}{col 31}{res}{space 2}-.1153496{col 43}{space 2} 1.021213{col 54}{space 1}   -0.11{col 63}{space 3}0.910{col 71}{space 4}-2.121524{col 84}{space 3} 1.890824
{txt}{space 21}vizcaya  {c |}{col 31}{res}{space 2} 2.000169{col 43}{space 2} 1.637123{col 54}{space 1}    1.22{col 63}{space 3}0.222{col 71}{space 4}-1.215961{col 84}{space 3} 5.216298
{txt}{space 22}zamora  {c |}{col 31}{res}{space 2} 1.280994{col 43}{space 2} 1.164957{col 54}{space 1}    1.10{col 63}{space 3}0.272{col 71}{space 4}-1.007567{col 84}{space 3} 3.569555
{txt}{space 20}zaragoza  {c |}{col 31}{res}{space 2}-1.221111{col 43}{space 2} 1.406271{col 54}{space 1}   -0.87{col 63}{space 3}0.386{col 71}{space 4}-3.983733{col 84}{space 3}  1.54151
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} 3.752535{col 43}{space 2} 3.640667{col 54}{space 1}    1.03{col 63}{space 3}0.303{col 71}{space 4} -3.39956{col 84}{space 3} 10.90463
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-2.0073051
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "All"

{txt}added macro:
           e(Election) : "{res:All}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_meta: reg var_votes_inc_ours var_votes_inc_ours

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       600
{txt}{hline 13}{c +}{hline 34}   F(1, 598)       = {res}        .
{txt}       Model {c |} {res} 32423.3892         1  32423.3892   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res}          0       598           0   {txt}R-squared       ={res}    1.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    1.0000
{txt}       Total {c |} {res} 32423.3892       599  54.1291974   {txt}Root MSE        =   {res}      0

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}var_votes_inc_ours{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var_votes_inc_ours {c |}{col 20}{res}{space 2}        1{col 32}{space 2}        .{col 43}{space 1}       .{col 52}{space 3}    .{col 60}{space 4}        .{col 73}{space 3}        .
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 4.44e-16{col 32}{space 2}        .{col 43}{space 1}       .{col 52}{space 3}    .{col 60}{space 4}        .{col 73}{space 3}        .
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-2.0073051
{txt}
{com}. estadd local Estimation "Meta"

{txt}added macro:
         e(Estimation) : "{res:Meta}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year ""

{txt}added macro:
               e(Year) : "{res:}"

{com}. estadd local Province ""

{txt}added macro:
           e(Province) : "{res:}"

{com}. estadd local Cluster ""

{txt}added macro:
            e(Cluster) : "{res:}"

{com}. estadd local Controls ""

{txt}added macro:
           e(Controls) : "{res:}"

{com}. estadd local Election "All"

{txt}added macro:
           e(Election) : "{res:All}"

{com}. estadd local Pop_weights ""

{txt}added macro:
        e(Pop_weights) : "{res:}"

{com}. 
.         
. * Table A9 - Electoral Results with Population Weights, by Election, Using Our Data
. esttab col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 col_4_all col_4_meta using ${c -(}tables{c )-}electoral_results_our_data_by_election_pw_inter.tex, ///
>                 keep(top_prizes_gdp_term_2)  ///
>                 nocon r2 ///
>                 mtitles se mtitles("Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." ///
>                                                         "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." ///
>                                                         "Vote Incumb." "Vote Incumb.")  ///
>                 coeflabels(top_prizes_gdp_term_2 "Cumulative Top Prizes")  ///
>                                         scalars("MeanDV Outcome Mean" "Estimation Estimation" "Data Data" "Year Year FEs" "Province Province FEs" "Controls Controls" "Cluster Cluster Province" "Election Election" "Pop_weights Pop. Weights")  ///
>         star(* 0.05 ** 0.01) b(%9.3f) replace
{res}{txt}(note: file Results/Tables_Electoral/electoral_results_our_data_by_election_pw_inter.tex not found)
(output written to {browse  `"Results/Tables_Electoral/electoral_results_our_data_by_election_pw_inter.tex"'})

{com}.                 
. 
.                 
. **----------------------------------------------------------------------------**
. *** META ANALYSIS (WITH POPULATION WEIGHTS)
. **----------------------------------------------------------------------------**
.                 
.                 
. * Full period
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_term_2]
{txt}  4{com}.     local se = _se[top_prizes_gdp_term_2]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_89:col_4_89} are active now)
(results {stata estimates replay col_4_93:col_4_93} are active now)
(results {stata estimates replay col_4_96:col_4_96} are active now)
(results {stata estimates replay col_4_00:col_4_00} are active now)
(results {stata estimates replay col_4_04:col_4_04} are active now)
(results {stata estimates replay col_4_08:col_4_08} are active now)
(results {stata estimates replay col_4_11:col_4_11} are active now)
(results {stata estimates replay col_4_15:col_4_15} are active now)
(results {stata estimates replay col_4_16:col_4_16} are active now)
(results {stata estimates replay col_4_19_4:col_4_19_4} are active now)
(results {stata estimates replay col_4_19_11:col_4_19_11} are active now)
(results {stata estimates replay col_4_23:col_4_23} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient
{res}{txt}
{com}. rename c2 stderr
{res}{txt}
{com}. 
. gen regression_pre = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression_pre = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression_pre{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
variable {bf}regression_pre{sf} was {bf}{res}str8{sf}{txt} now {bf}{res}str10{sf}
{txt}(1 real change made)
variable {bf}regression_pre{sf} was {bf}{res}str10{sf}{txt} now {bf}{res}str11{sf}
{txt}(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient stderr , studylabel(regression_pre)
{txt}(638 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}12
{col 8}{txt}Study label:  {res}regression_pre
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient
{txt}{col 11}Std. Err.:  {res}stderr
{txt}{col 9}Study label:  {res}regression_pre

{txt}Meta-analysis summary{col 43}Number of studies = {res}    12
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 0.0323
{txt}{col 53}I2 (%) = {res}  11.85
{txt}{col 57}H2 = {res}   1.13

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_89{col 19}{c |}{res}{space 6}   -0.163{col 35}{space 3}   -0.736{col 47}{space 3}    0.410{col 59}{space 5}19.70
{col 1}{txt}         col_4_93{col 19}{c |}{res}{space 6}   -2.144{col 35}{space 3}   -4.070{col 47}{space 3}   -0.218{col 59}{space 5} 2.32
{col 1}{txt}         col_4_96{col 19}{c |}{res}{space 6}    1.953{col 35}{space 3}    0.297{col 47}{space 3}    3.609{col 59}{space 5} 3.11
{col 1}{txt}         col_4_00{col 19}{c |}{res}{space 6}    0.921{col 35}{space 3}   -0.712{col 47}{space 3}    2.554{col 59}{space 5} 3.19
{col 1}{txt}         col_4_04{col 19}{c |}{res}{space 6}    0.661{col 35}{space 3}   -0.569{col 47}{space 3}    1.891{col 59}{space 5} 5.44
{col 1}{txt}         col_4_08{col 19}{c |}{res}{space 6}    0.705{col 35}{space 3}   -0.195{col 47}{space 3}    1.605{col 59}{space 5} 9.53
{col 1}{txt}         col_4_11{col 19}{c |}{res}{space 6}   -0.456{col 35}{space 3}   -3.416{col 47}{space 3}    2.504{col 59}{space 5} 1.00
{col 1}{txt}         col_4_15{col 19}{c |}{res}{space 6}   -0.495{col 35}{space 3}   -2.817{col 47}{space 3}    1.827{col 59}{space 5} 1.61
{col 1}{txt}         col_4_16{col 19}{c |}{res}{space 6}    0.393{col 35}{space 3}    0.014{col 47}{space 3}    0.772{col 59}{space 5}33.25
{col 1}{txt}       col_4_19_4{col 19}{c |}{res}{space 6}    0.123{col 35}{space 3}   -0.767{col 47}{space 3}    1.014{col 59}{space 5} 9.72
{col 1}{txt}      col_4_19_11{col 19}{c |}{res}{space 6}   -0.042{col 35}{space 3}   -0.918{col 47}{space 3}    0.834{col 59}{space 5} 9.99
{col 1}{txt}         col_4_23{col 19}{c |}{res}{space 6}    1.210{col 35}{space 3}   -1.594{col 47}{space 3}    4.015{col 59}{space 5} 1.11
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}    0.251{col 35}{space 3}   -0.048{col 47}{space 3}    0.549
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}1.65{txt}{col 50}Prob > |z| = {res}0.0996
{txt}Test of homogeneity: Q = chi2({res}11{txt}) = {res}16.16{txt}{col 52}Prob > Q = {res}0.1352
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient
{txt}{col 11}Std. Err.:  {res}stderr
{txt}{col 9}Study label:  {res}regression_pre

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_our_weights.png", replace                    
{txt}(note: file Results/Figures_Electoral/forestplot_our_weights.png not found)
(file Results/Figures_Electoral/forestplot_our_weights.png written in PNG format)

{com}.                 
.                 
. * Replication period
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_term_2]
{txt}  4{com}.     local se = _se[top_prizes_gdp_term_2]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_89:col_4_89} are active now)
(results {stata estimates replay col_4_93:col_4_93} are active now)
(results {stata estimates replay col_4_96:col_4_96} are active now)
(results {stata estimates replay col_4_00:col_4_00} are active now)
(results {stata estimates replay col_4_04:col_4_04} are active now)
(results {stata estimates replay col_4_08:col_4_08} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient_pre
{res}{txt}
{com}. rename c2 stderr_pre
{res}{txt}
{com}. 
. gen regression_pre_w = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression_pre_w = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression_pre_w{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient_pre stderr_pre , studylabel(regression_pre_w)
{txt}(644 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}6
{col 8}{txt}Study label:  {res}regression_pre_w
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient_pre

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr_pre
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_pre
{txt}{col 11}Std. Err.:  {res}stderr_pre
{txt}{col 9}Study label:  {res}regression_pre_w

{txt}Meta-analysis summary{col 43}Number of studies = {res}     6
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 0.6967
{txt}{col 53}I2 (%) = {res}  68.19
{txt}{col 57}H2 = {res}   3.14

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_89{col 19}{c |}{res}{space 6}   -0.163{col 35}{space 3}   -0.736{col 47}{space 3}    0.410{col 59}{space 5}24.00
{col 1}{txt}         col_4_93{col 19}{c |}{res}{space 6}   -2.144{col 35}{space 3}   -4.070{col 47}{space 3}   -0.218{col 59}{space 5}11.29
{col 1}{txt}         col_4_96{col 19}{c |}{res}{space 6}    1.953{col 35}{space 3}    0.297{col 47}{space 3}    3.609{col 59}{space 5}13.31
{col 1}{txt}         col_4_00{col 19}{c |}{res}{space 6}    0.921{col 35}{space 3}   -0.712{col 47}{space 3}    2.554{col 59}{space 5}13.50
{col 1}{txt}         col_4_04{col 19}{c |}{res}{space 6}    0.661{col 35}{space 3}   -0.569{col 47}{space 3}    1.891{col 59}{space 5}17.22
{col 1}{txt}         col_4_08{col 19}{c |}{res}{space 6}    0.705{col 35}{space 3}   -0.195{col 47}{space 3}    1.605{col 59}{space 5}20.68
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}    0.363{col 35}{space 3}   -0.486{col 47}{space 3}    1.212
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}0.84{txt}{col 50}Prob > |z| = {res}0.4025
{txt}Test of homogeneity: Q = chi2({res}5{txt}) = {res}14.03{txt}{col 52}Prob > Q = {res}0.0154
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_pre
{txt}{col 11}Std. Err.:  {res}stderr_pre
{txt}{col 9}Study label:  {res}regression_pre_w

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_pre_weights.png", replace            
{txt}(note: file Results/Figures_Electoral/forestplot_pre_weights.png not found)
(file Results/Figures_Electoral/forestplot_pre_weights.png written in PNG format)

{com}. 
. 
. * Out-of-sample
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_term_2]
{txt}  4{com}.     local se = _se[top_prizes_gdp_term_2]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_11:col_4_11} are active now)
(results {stata estimates replay col_4_15:col_4_15} are active now)
(results {stata estimates replay col_4_16:col_4_16} are active now)
(results {stata estimates replay col_4_19_4:col_4_19_4} are active now)
(results {stata estimates replay col_4_19_11:col_4_19_11} are active now)
(results {stata estimates replay col_4_23:col_4_23} are active now)

{com}. 
. * Save the results to a new dataset
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient_post
{res}{txt}
{com}. rename c2 stderr_post
{res}{txt}
{com}. 
. * Add regression names
. gen regression_post_w = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression_post_w = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression_post_w{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
variable {bf}regression_post_w{sf} was {bf}{res}str8{sf}{txt} now {bf}{res}str10{sf}
{txt}(1 real change made)
variable {bf}regression_post_w{sf} was {bf}{res}str10{sf}{txt} now {bf}{res}str11{sf}
{txt}(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient_post stderr_post , studylabel(regression_post_w)
{txt}(644 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}6
{col 8}{txt}Study label:  {res}regression_post_w
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient_post

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr_post
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_post
{txt}{col 11}Std. Err.:  {res}stderr_post
{txt}{col 9}Study label:  {res}regression_post_w

{txt}Meta-analysis summary{col 43}Number of studies = {res}     6
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 0.0000
{txt}{col 53}I2 (%) = {res}   0.00
{txt}{col 57}H2 = {res}   1.00

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_11{col 19}{c |}{res}{space 6}   -0.456{col 35}{space 3}   -3.416{col 47}{space 3}    2.504{col 59}{space 5} 1.15
{col 1}{txt}         col_4_15{col 19}{c |}{res}{space 6}   -0.495{col 35}{space 3}   -2.817{col 47}{space 3}    1.827{col 59}{space 5} 1.86
{col 1}{txt}         col_4_16{col 19}{c |}{res}{space 6}    0.393{col 35}{space 3}    0.014{col 47}{space 3}    0.772{col 59}{space 5}69.91
{col 1}{txt}       col_4_19_4{col 19}{c |}{res}{space 6}    0.123{col 35}{space 3}   -0.767{col 47}{space 3}    1.014{col 59}{space 5}12.69
{col 1}{txt}      col_4_19_11{col 19}{c |}{res}{space 6}   -0.042{col 35}{space 3}   -0.918{col 47}{space 3}    0.834{col 59}{space 5}13.10
{col 1}{txt}         col_4_23{col 19}{c |}{res}{space 6}    1.210{col 35}{space 3}   -1.594{col 47}{space 3}    4.015{col 59}{space 5} 1.28
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}    0.286{col 35}{space 3}   -0.031{col 47}{space 3}    0.603
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}1.77{txt}{col 50}Prob > |z| = {res}0.0772
{txt}Test of homogeneity: Q = chi2({res}5{txt}) = {res}2.07{txt}{col 52}Prob > Q = {res}0.8400
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_post
{txt}{col 11}Std. Err.:  {res}stderr_post
{txt}{col 9}Study label:  {res}regression_post_w

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_post_weights.png", replace   
{txt}(note: file Results/Figures_Electoral/forestplot_post_weights.png not found)
(file Results/Figures_Electoral/forestplot_post_weights.png written in PNG format)

{com}. 
.                 
. restore
{txt}
{com}. 
. 
. * Table A12: Estimated Effects of Lottery Winnings on Province-Level Vote Share for the Incumbent Party - Meta Analyses: created manually using results of meta analyses above
. 
. 
. 
. 
. **----------------------------------------------------------------------------**
. *** OUR DATA (NO POPULATION WEIGHTS), ONLY SAME YEAR'S PRIZES AND EXPENDITURE
. **----------------------------------------------------------------------------**
. preserve
{txt}
{com}. 
. global controls_ours D_unemployment_rate_2 D_gdp_pc_2 D_cpi_2 D_housing_price_2
{txt}
{com}. replace D_housing_price_2=housing_price_growth_term_1 if D_housing_price_==.
{txt}(100 real changes made)

{com}. 
. 
. eststo col_4_89: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==1989

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}    10.56
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.3051
                                                {txt}Root MSE          =    {res} 2.3032

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} -3.06098{col 36}{space 2} .8678427{col 47}{space 1}   -3.53{col 56}{space 3}0.001{col 64}{space 4}-4.811151{col 77}{space 3}-1.310808
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2}-2.465372{col 36}{space 2} 5.950049{col 47}{space 1}   -0.41{col 56}{space 3}0.681{col 64}{space 4}-14.46479{col 77}{space 3} 9.534046
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0942003{col 36}{space 2} .1302529{col 47}{space 1}    0.72{col 56}{space 3}0.473{col 64}{space 4}-.1684797{col 77}{space 3} .3568804
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0789046{col 36}{space 2} .0430188{col 47}{space 1}    1.83{col 56}{space 3}0.074{col 64}{space 4}-.0078511{col 77}{space 3} .1656602
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.5653271{col 36}{space 2} .1676864{col 47}{space 1}   -3.37{col 56}{space 3}0.002{col 64}{space 4}-.9034989{col 77}{space 3}-.2271554
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}  -.05561{col 36}{space 2} .0368999{col 47}{space 1}   -1.51{col 56}{space 3}0.139{col 64}{space 4}-.1300257{col 77}{space 3} .0188056
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 8.475233{col 36}{space 2} 3.430511{col 47}{space 1}    2.47{col 56}{space 3}0.018{col 64}{space 4} 1.556949{col 77}{space 3} 15.39352
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-2.6632372
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1989"

{txt}added macro:
           e(Election) : "{res:1989}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_93: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==1993

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     4.61
                                                {txt}Prob > F          = {res}    0.0011
                                                {txt}R-squared         = {res}    0.2901
                                                {txt}Root MSE          =    {res} 2.4924

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-1.145795{col 36}{space 2}  .976132{col 47}{space 1}   -1.17{col 56}{space 3}0.247{col 64}{space 4}-3.114353{col 77}{space 3} .8227629
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} 4.582302{col 36}{space 2} 4.973694{col 47}{space 1}    0.92{col 56}{space 3}0.362{col 64}{space 4}-5.448109{col 77}{space 3} 14.61271
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.3794296{col 36}{space 2} .1276465{col 47}{space 1}   -2.97{col 56}{space 3}0.005{col 64}{space 4}-.6368532{col 77}{space 3} -.122006
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0837859{col 36}{space 2} .0515183{col 47}{space 1}    1.63{col 56}{space 3}0.111{col 64}{space 4}-.0201107{col 77}{space 3} .1876826
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.0279084{col 36}{space 2} .1346972{col 47}{space 1}   -0.21{col 56}{space 3}0.837{col 64}{space 4}-.2995513{col 77}{space 3} .2437344
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .2514161{col 36}{space 2} .0702168{col 47}{space 1}    3.58{col 56}{space 3}0.001{col 64}{space 4} .1098104{col 77}{space 3} .3930219
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-.5433473{col 36}{space 2} 4.052015{col 47}{space 1}   -0.13{col 56}{space 3}0.894{col 64}{space 4}-8.715015{col 77}{space 3}  7.62832
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-.75916344
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1993"

{txt}added macro:
           e(Election) : "{res:1993}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_96: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==1996

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     4.46
                                                {txt}Prob > F          = {res}    0.0014
                                                {txt}R-squared         = {res}    0.2447
                                                {txt}Root MSE          =    {res} 2.6976

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} 1.636366{col 36}{space 2} .6479562{col 47}{space 1}    2.53{col 56}{space 3}0.015{col 64}{space 4} .3296381{col 77}{space 3} 2.943094
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} .7285553{col 36}{space 2} 5.254486{col 47}{space 1}    0.14{col 56}{space 3}0.890{col 64}{space 4}-9.868125{col 77}{space 3} 11.32524
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0326169{col 36}{space 2} .1057338{col 47}{space 1}    0.31{col 56}{space 3}0.759{col 64}{space 4}-.1806157{col 77}{space 3} .2458495
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0692154{col 36}{space 2} .0464563{col 47}{space 1}    1.49{col 56}{space 3}0.144{col 64}{space 4}-.0244727{col 77}{space 3} .1629034
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.0201994{col 36}{space 2} .3318043{col 47}{space 1}   -0.06{col 56}{space 3}0.952{col 64}{space 4}-.6893465{col 77}{space 3} .6489477
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .3671817{col 36}{space 2}  .110021{col 47}{space 1}    3.34{col 56}{space 3}0.002{col 64}{space 4} .1453032{col 77}{space 3} .5890601
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-.4818834{col 36}{space 2} 5.079505{col 47}{space 1}   -0.09{col 56}{space 3}0.925{col 64}{space 4}-10.72568{col 77}{space 3} 9.761915
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-1.1425475
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1996"

{txt}added macro:
           e(Election) : "{res:1996}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_00: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==2000

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     3.05
                                                {txt}Prob > F          = {res}    0.0141
                                                {txt}R-squared         = {res}    0.2043
                                                {txt}Root MSE          =    {res} 2.7696

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} 2.001672{col 36}{space 2} .9316084{col 47}{space 1}    2.15{col 56}{space 3}0.037{col 64}{space 4} .1229048{col 77}{space 3} 3.880439
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2}-8.762494{col 36}{space 2} 4.513925{col 47}{space 1}   -1.94{col 56}{space 3}0.059{col 64}{space 4}-17.86569{col 77}{space 3} .3407041
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.1822471{col 36}{space 2} .1334939{col 47}{space 1}   -1.37{col 56}{space 3}0.179{col 64}{space 4}-.4514632{col 77}{space 3} .0869689
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.0118168{col 36}{space 2} .0273977{col 47}{space 1}   -0.43{col 56}{space 3}0.668{col 64}{space 4}-.0670696{col 77}{space 3}  .043436
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}   .44021{col 36}{space 2} .3992105{col 47}{space 1}    1.10{col 56}{space 3}0.276{col 64}{space 4}-.3648748{col 77}{space 3} 1.245295
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0141345{col 36}{space 2} .0389875{col 47}{space 1}    0.36{col 56}{space 3}0.719{col 64}{space 4}-.0644913{col 77}{space 3} .0927602
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 2.406645{col 36}{space 2} 3.898811{col 47}{space 1}    0.62{col 56}{space 3}0.540{col 64}{space 4}-5.456057{col 77}{space 3} 10.26935
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}5.2046794
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2000"

{txt}added macro:
           e(Election) : "{res:2000}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_04: reg var_votes_inc_reppkg top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==2004

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     1.07
                                                {txt}Prob > F          = {res}    0.3935
                                                {txt}R-squared         = {res}    0.1267
                                                {txt}Root MSE          =    {res} 2.3395

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}  var_votes_inc_reppkg{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-.5183136{col 36}{space 2} .8067817{col 47}{space 1}   -0.64{col 56}{space 3}0.524{col 64}{space 4}-2.145344{col 77}{space 3} 1.108717
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} 6.901043{col 36}{space 2} 3.963909{col 47}{space 1}    1.74{col 56}{space 3}0.089{col 64}{space 4}-1.092942{col 77}{space 3} 14.89503
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.1201886{col 36}{space 2} .1108185{col 47}{space 1}   -1.08{col 56}{space 3}0.284{col 64}{space 4}-.3436754{col 77}{space 3} .1032983
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.0011419{col 36}{space 2} .0649325{col 47}{space 1}   -0.02{col 56}{space 3}0.986{col 64}{space 4}-.1320907{col 77}{space 3} .1298068
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.0985201{col 36}{space 2} .3889859{col 47}{space 1}   -0.25{col 56}{space 3}0.801{col 64}{space 4}-.8829848{col 77}{space 3} .6859447
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0037913{col 36}{space 2} .0169079{col 47}{space 1}    0.22{col 56}{space 3}0.824{col 64}{space 4}-.0303068{col 77}{space 3} .0378894
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-7.764453{col 36}{space 2}  4.74438{col 47}{space 1}   -1.64{col 56}{space 3}0.109{col 64}{space 4}-17.33241{col 77}{space 3} 1.803502
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-6.3910645
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2004"

{txt}added macro:
           e(Election) : "{res:2004}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_08: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==2008

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.55
                                                {txt}Prob > F          = {res}    0.0338
                                                {txt}R-squared         = {res}    0.1433
                                                {txt}Root MSE          =    {res} 4.2389

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} 1.186433{col 36}{space 2} .8823612{col 47}{space 1}    1.34{col 56}{space 3}0.186{col 64}{space 4}-.5930175{col 77}{space 3} 2.965884
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2}-4.552358{col 36}{space 2} 6.240728{col 47}{space 1}   -0.73{col 56}{space 3}0.470{col 64}{space 4}-17.13799{col 77}{space 3}  8.03327
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.3166064{col 36}{space 2} .1750291{col 47}{space 1}   -1.81{col 56}{space 3}0.077{col 64}{space 4}-.6695863{col 77}{space 3} .0363735
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.0647462{col 36}{space 2}  .153922{col 47}{space 1}   -0.42{col 56}{space 3}0.676{col 64}{space 4}-.3751594{col 77}{space 3}  .245667
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .8512561{col 36}{space 2} .7777058{col 47}{space 1}    1.09{col 56}{space 3}0.280{col 64}{space 4}-.7171371{col 77}{space 3} 2.419649
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0351509{col 36}{space 2} .0539803{col 47}{space 1}   -0.65{col 56}{space 3}0.518{col 64}{space 4}-.1440126{col 77}{space 3} .0737108
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-4.610768{col 36}{space 2} 10.10805{col 47}{space 1}   -0.46{col 56}{space 3}0.651{col 64}{space 4}-24.99559{col 77}{space 3} 15.77405
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}2.1097373
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2008"

{txt}added macro:
           e(Election) : "{res:2008}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_11: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==2011

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     3.93
                                                {txt}Prob > F          = {res}    0.0032
                                                {txt}R-squared         = {res}    0.2673
                                                {txt}Root MSE          =    {res} 1.9517

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-.2004903{col 36}{space 2} 2.787981{col 47}{space 1}   -0.07{col 56}{space 3}0.943{col 64}{space 4}-5.822991{col 77}{space 3}  5.42201
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} 8.188973{col 36}{space 2} 2.246447{col 47}{space 1}    3.65{col 56}{space 3}0.001{col 64}{space 4}  3.65858{col 77}{space 3} 12.71937
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0746347{col 36}{space 2} .1179046{col 47}{space 1}    0.63{col 56}{space 3}0.530{col 64}{space 4}-.1631427{col 77}{space 3}  .312412
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.1160975{col 36}{space 2} .0873176{col 47}{space 1}   -1.33{col 56}{space 3}0.191{col 64}{space 4}-.2921903{col 77}{space 3} .0599954
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.5961419{col 36}{space 2} .3595342{col 47}{space 1}   -1.66{col 56}{space 3}0.105{col 64}{space 4}-1.321212{col 77}{space 3} .1289279
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0881352{col 36}{space 2} .0467927{col 47}{space 1}    1.88{col 56}{space 3}0.066{col 64}{space 4}-.0062312{col 77}{space 3} .1825017
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-12.94039{col 36}{space 2} 2.733094{col 47}{space 1}   -4.73{col 56}{space 3}0.000{col 64}{space 4} -18.4522{col 77}{space 3}-7.428578
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-14.61119
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2011"

{txt}added macro:
           e(Election) : "{res:2011}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_15: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==2015

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     5.19
                                                {txt}Prob > F          = {res}    0.0004
                                                {txt}R-squared         = {res}    0.3348
                                                {txt}Root MSE          =    {res}  3.799

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-19.39767{col 36}{space 2} 5.396134{col 47}{space 1}   -3.59{col 56}{space 3}0.001{col 64}{space 4}-30.28001{col 77}{space 3}-8.515331
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} -6.24617{col 36}{space 2} 5.084087{col 47}{space 1}   -1.23{col 56}{space 3}0.226{col 64}{space 4}-16.49921{col 77}{space 3} 4.006867
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .7171938{col 36}{space 2} .2082486{col 47}{space 1}    3.44{col 56}{space 3}0.001{col 64}{space 4} .2972205{col 77}{space 3} 1.137167
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0314388{col 36}{space 2} .1497422{col 47}{space 1}    0.21{col 56}{space 3}0.835{col 64}{space 4}-.2705452{col 77}{space 3} .3334228
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} 2.107189{col 36}{space 2} .8615402{col 47}{space 1}    2.45{col 56}{space 3}0.019{col 64}{space 4}  .369728{col 77}{space 3} 3.844651
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0271646{col 36}{space 2} .1001916{col 47}{space 1}    0.27{col 56}{space 3}0.788{col 64}{space 4} -.174891{col 77}{space 3} .2292202
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}  -15.379{col 36}{space 2}  2.39414{col 47}{space 1}   -6.42{col 56}{space 3}0.000{col 64}{space 4}-20.20724{col 77}{space 3}-10.55075
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-15.111396
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2015"

{txt}added macro:
           e(Election) : "{res:2015}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_16: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==2016

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     3.15
                                                {txt}Prob > F          = {res}    0.0118
                                                {txt}R-squared         = {res}    0.2262
                                                {txt}Root MSE          =    {res} 1.1778

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} .1999002{col 36}{space 2} .1544842{col 47}{space 1}    1.29{col 56}{space 3}0.203{col 64}{space 4}-.1116469{col 77}{space 3} .5114473
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} 3.837784{col 36}{space 2} 1.217568{col 47}{space 1}    3.15{col 56}{space 3}0.003{col 64}{space 4} 1.382324{col 77}{space 3} 6.293243
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.0715215{col 36}{space 2} .0864349{col 47}{space 1}   -0.83{col 56}{space 3}0.413{col 64}{space 4}-.2458342{col 77}{space 3} .1027911
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}  .059064{col 36}{space 2} .0867981{col 47}{space 1}    0.68{col 56}{space 3}0.500{col 64}{space 4} -.115981{col 77}{space 3} .2341089
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} -1.51833{col 36}{space 2} .8637322{col 47}{space 1}   -1.76{col 56}{space 3}0.086{col 64}{space 4}-3.260212{col 77}{space 3} .2235523
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0241291{col 36}{space 2}  .045372{col 47}{space 1}   -0.53{col 56}{space 3}0.598{col 64}{space 4}-.1156304{col 77}{space 3} .0673723
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 5.261351{col 36}{space 2}  1.54196{col 47}{space 1}    3.41{col 56}{space 3}0.001{col 64}{space 4} 2.151692{col 77}{space 3} 8.371011
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}4.318167
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2016"

{txt}added macro:
           e(Election) : "{res:2016}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_19_4: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==2019 & month==4

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.67
                                                {txt}Prob > F          = {res}    0.0274
                                                {txt}R-squared         = {res}    0.1923
                                                {txt}Root MSE          =    {res} 2.0348

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-.1027819{col 36}{space 2} .3026764{col 47}{space 1}   -0.34{col 56}{space 3}0.736{col 64}{space 4}-.7131871{col 77}{space 3} .5076233
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} .8399827{col 36}{space 2} 2.068216{col 47}{space 1}    0.41{col 56}{space 3}0.687{col 64}{space 4}-3.330972{col 77}{space 3} 5.010938
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .3603784{col 36}{space 2} .1020686{col 47}{space 1}    3.53{col 56}{space 3}0.001{col 64}{space 4} .1545373{col 77}{space 3} .5662194
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0303462{col 36}{space 2}  .099154{col 47}{space 1}    0.31{col 56}{space 3}0.761{col 64}{space 4}-.1696169{col 77}{space 3} .2303093
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .4824515{col 36}{space 2} .6582543{col 47}{space 1}    0.73{col 56}{space 3}0.468{col 64}{space 4}-.8450449{col 77}{space 3} 1.809948
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}  .053304{col 36}{space 2} .0424749{col 47}{space 1}    1.25{col 56}{space 3}0.216{col 64}{space 4}-.0323549{col 77}{space 3} .1389629
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 4.925567{col 36}{space 2} 2.242098{col 47}{space 1}    2.20{col 56}{space 3}0.033{col 64}{space 4} .4039464{col 77}{space 3} 9.447188
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}5.7350554
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2019 (4)"

{txt}added macro:
           e(Election) : "{res:2019 (4)}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_19_11: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==2019 & month==11

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     6.42
                                                {txt}Prob > F          = {res}    0.0001
                                                {txt}R-squared         = {res}    0.3238
                                                {txt}Root MSE          =    {res} 1.4487

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} .0081948{col 36}{space 2} .6335938{col 47}{space 1}    0.01{col 56}{space 3}0.990{col 64}{space 4}-1.269569{col 77}{space 3} 1.285958
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} 4.348721{col 36}{space 2} 2.208262{col 47}{space 1}    1.97{col 56}{space 3}0.055{col 64}{space 4}-.1046639{col 77}{space 3} 8.802105
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0328497{col 36}{space 2} .0868753{col 47}{space 1}    0.38{col 56}{space 3}0.707{col 64}{space 4}-.1423512{col 77}{space 3} .2080505
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .1191345{col 36}{space 2} .0527986{col 47}{space 1}    2.26{col 56}{space 3}0.029{col 64}{space 4}  .012656{col 77}{space 3}  .225613
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.3960247{col 36}{space 2} .3482482{col 47}{space 1}   -1.14{col 56}{space 3}0.262{col 64}{space 4}-1.098334{col 77}{space 3} .3062847
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0599944{col 36}{space 2} .0716438{col 47}{space 1}   -0.84{col 56}{space 3}0.407{col 64}{space 4}-.2044779{col 77}{space 3} .0844891
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-.2294099{col 36}{space 2}  1.29704{col 47}{space 1}   -0.18{col 56}{space 3}0.860{col 64}{space 4}-2.845141{col 77}{space 3} 2.386321
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-.16204425
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2019 (11)"

{txt}added macro:
           e(Election) : "{res:2019 (11)}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_23: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours, robust , if year==2023

{txt}Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     5.10
                                                {txt}Prob > F          = {res}    0.0005
                                                {txt}R-squared         = {res}    0.3303
                                                {txt}Root MSE          =    {res} 3.7208

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-1.902003{col 36}{space 2} 2.362014{col 47}{space 1}   -0.81{col 56}{space 3}0.425{col 64}{space 4}-6.665458{col 77}{space 3} 2.861452
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2}-9.900371{col 36}{space 2} 4.656595{col 47}{space 1}   -2.13{col 56}{space 3}0.039{col 64}{space 4}-19.29129{col 77}{space 3}-.5094522
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .1518986{col 36}{space 2} .2432491{col 47}{space 1}    0.62{col 56}{space 3}0.536{col 64}{space 4}  -.33866{col 77}{space 3} .6424572
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} -.117017{col 36}{space 2} .1810354{col 47}{space 1}   -0.65{col 56}{space 3}0.521{col 64}{space 4}-.4821097{col 77}{space 3} .2480757
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-1.237706{col 36}{space 2} .6908353{col 47}{space 1}   -1.79{col 56}{space 3}0.080{col 64}{space 4}-2.630908{col 77}{space 3}  .155496
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0408289{col 36}{space 2} .1067838{col 47}{space 1}    0.38{col 56}{space 3}0.704{col 64}{space 4}-.1745212{col 77}{space 3} .2561791
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 20.71053{col 36}{space 2} 9.038729{col 47}{space 1}    2.29{col 56}{space 3}0.027{col 64}{space 4} 2.482199{col 77}{space 3} 38.93887
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}2.4617514
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2023"

{txt}added macro:
           e(Election) : "{res:2023}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_all: reg var_votes_inc_ours top_prizes_gdp_ours_c c.expenditure_gdp_ours_c##i.year $controls_ours i.province_num, robust

{txt}Linear regression                               Number of obs     = {res}       600
                                                {txt}F(75, 524)        =  {res}    53.75
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8447
                                                {txt}Root MSE          =    {res} 3.0995

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}           var_votes_inc_ours{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}top_prizes_gdp_ours_c {c |}{col 31}{res}{space 2}  .312861{col 43}{space 2} .4268205{col 54}{space 1}    0.73{col 63}{space 3}0.464{col 71}{space 4}-.5256284{col 84}{space 3} 1.151351
{txt}{space 7}expenditure_gdp_ours_c {c |}{col 31}{res}{space 2}-8.759871{col 43}{space 2}  7.79536{col 54}{space 1}   -1.12{col 63}{space 3}0.262{col 71}{space 4}-24.07387{col 84}{space 3} 6.554125
{txt}{space 29} {c |}
{space 25}year {c |}
{space 24}1993  {c |}{col 31}{res}{space 2}  2.99158{col 43}{space 2} 2.238715{col 54}{space 1}    1.34{col 63}{space 3}0.182{col 71}{space 4}-1.406379{col 84}{space 3} 7.389539
{txt}{space 24}1996  {c |}{col 31}{res}{space 2} .0285434{col 43}{space 2} 2.029424{col 54}{space 1}    0.01{col 63}{space 3}0.989{col 71}{space 4}-3.958264{col 84}{space 3} 4.015351
{txt}{space 24}2000  {c |}{col 31}{res}{space 2} 7.402847{col 43}{space 2} 2.263906{col 54}{space 1}    3.27{col 63}{space 3}0.001{col 71}{space 4} 2.955401{col 84}{space 3} 11.85029
{txt}{space 24}2004  {c |}{col 31}{res}{space 2}-8.468676{col 43}{space 2} 2.366799{col 54}{space 1}   -3.58{col 63}{space 3}0.000{col 71}{space 4}-13.11826{col 84}{space 3}-3.819096
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} 4.000037{col 43}{space 2} 2.640845{col 54}{space 1}    1.51{col 63}{space 3}0.130{col 71}{space 4}-1.187907{col 84}{space 3} 9.187982
{txt}{space 24}2011  {c |}{col 31}{res}{space 2}-16.12368{col 43}{space 2} 2.537359{col 54}{space 1}   -6.35{col 63}{space 3}0.000{col 71}{space 4}-21.10832{col 84}{space 3}-11.13903
{txt}{space 24}2015  {c |}{col 31}{res}{space 2}-16.42959{col 43}{space 2} 2.930649{col 54}{space 1}   -5.61{col 63}{space 3}0.000{col 71}{space 4}-22.18685{col 84}{space 3}-10.67232
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} 1.102699{col 43}{space 2} 2.680502{col 54}{space 1}    0.41{col 63}{space 3}0.681{col 71}{space 4}-4.163152{col 84}{space 3}  6.36855
{txt}{space 24}2019  {c |}{col 31}{res}{space 2}-.7293664{col 43}{space 2} 2.622439{col 54}{space 1}   -0.28{col 63}{space 3}0.781{col 71}{space 4}-5.881152{col 84}{space 3} 4.422419
{txt}{space 24}2023  {c |}{col 31}{res}{space 2} 7.618555{col 43}{space 2} 2.239319{col 54}{space 1}    3.40{col 63}{space 3}0.001{col 71}{space 4} 3.219409{col 84}{space 3}  12.0177
{txt}{space 29} {c |}
year#c.expenditure_gdp_ours_c {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} 8.387889{col 43}{space 2} 7.742487{col 54}{space 1}    1.08{col 63}{space 3}0.279{col 71}{space 4}-6.822239{col 84}{space 3} 23.59802
{txt}{space 24}1996  {c |}{col 31}{res}{space 2} 5.759177{col 43}{space 2} 7.530623{col 54}{space 1}    0.76{col 63}{space 3}0.445{col 71}{space 4}-9.034744{col 84}{space 3}  20.5531
{txt}{space 24}2000  {c |}{col 31}{res}{space 2}-4.193049{col 43}{space 2}  7.48399{col 54}{space 1}   -0.56{col 63}{space 3}0.576{col 71}{space 4}-18.89536{col 84}{space 3} 10.50926
{txt}{space 24}2004  {c |}{col 31}{res}{space 2} 12.06292{col 43}{space 2} 7.802889{col 54}{space 1}    1.55{col 63}{space 3}0.123{col 71}{space 4}-3.265867{col 84}{space 3} 27.39171
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} 1.152906{col 43}{space 2} 8.431524{col 54}{space 1}    0.14{col 63}{space 3}0.891{col 71}{space 4}-15.41083{col 84}{space 3} 17.71665
{txt}{space 24}2011  {c |}{col 31}{res}{space 2} 11.54117{col 43}{space 2} 7.243445{col 54}{space 1}    1.59{col 63}{space 3}0.112{col 71}{space 4}-2.688588{col 84}{space 3} 25.77093
{txt}{space 24}2015  {c |}{col 31}{res}{space 2} 4.454621{col 43}{space 2}  7.72418{col 54}{space 1}    0.58{col 63}{space 3}0.564{col 71}{space 4}-10.71954{col 84}{space 3} 19.62878
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} 9.360405{col 43}{space 2}  7.00799{col 54}{space 1}    1.34{col 63}{space 3}0.182{col 71}{space 4}-4.406802{col 84}{space 3} 23.12761
{txt}{space 24}2019  {c |}{col 31}{res}{space 2} 10.60653{col 43}{space 2} 7.122044{col 54}{space 1}    1.49{col 63}{space 3}0.137{col 71}{space 4} -3.38474{col 84}{space 3} 24.59779
{txt}{space 24}2023  {c |}{col 31}{res}{space 2}-8.962687{col 43}{space 2} 7.589851{col 54}{space 1}   -1.18{col 63}{space 3}0.238{col 71}{space 4}-23.87296{col 84}{space 3} 5.947586
{txt}{space 29} {c |}
{space 8}D_unemployment_rate_2 {c |}{col 31}{res}{space 2}-.0449562{col 43}{space 2} .0480333{col 54}{space 1}   -0.94{col 63}{space 3}0.350{col 71}{space 4}-.1393178{col 84}{space 3} .0494053
{txt}{space 19}D_gdp_pc_2 {c |}{col 31}{res}{space 2} .0146259{col 43}{space 2} .0196926{col 54}{space 1}    0.74{col 63}{space 3}0.458{col 71}{space 4}-.0240601{col 84}{space 3}  .053312
{txt}{space 22}D_cpi_2 {c |}{col 31}{res}{space 2}  -.27124{col 43}{space 2} .1247939{col 54}{space 1}   -2.17{col 63}{space 3}0.030{col 71}{space 4}-.5163978{col 84}{space 3}-.0260823
{txt}{space 12}D_housing_price_2 {c |}{col 31}{res}{space 2}  .021898{col 43}{space 2} .0151949{col 54}{space 1}    1.44{col 63}{space 3}0.150{col 71}{space 4}-.0079524{col 84}{space 3} .0517484
{txt}{space 29} {c |}
{space 17}province_num {c |}
{space 23}alava  {c |}{col 31}{res}{space 2} .5712824{col 43}{space 2}  1.65393{col 54}{space 1}    0.35{col 63}{space 3}0.730{col 71}{space 4}-2.677866{col 84}{space 3} 3.820431
{txt}{space 20}albacete  {c |}{col 31}{res}{space 2}-.4476475{col 43}{space 2} 1.001827{col 54}{space 1}   -0.45{col 63}{space 3}0.655{col 71}{space 4}-2.415738{col 84}{space 3} 1.520443
{txt}{space 20}alicante  {c |}{col 31}{res}{space 2} -.326188{col 43}{space 2} 1.292062{col 54}{space 1}   -0.25{col 63}{space 3}0.801{col 71}{space 4}-2.864446{col 84}{space 3}  2.21207
{txt}{space 21}almeria  {c |}{col 31}{res}{space 2}-1.380123{col 43}{space 2} 1.357629{col 54}{space 1}   -1.02{col 63}{space 3}0.310{col 71}{space 4}-4.047187{col 84}{space 3}  1.28694
{txt}{space 20}asturias  {c |}{col 31}{res}{space 2}  1.31373{col 43}{space 2} 1.430104{col 54}{space 1}    0.92{col 63}{space 3}0.359{col 71}{space 4}-1.495712{col 84}{space 3} 4.123171
{txt}{space 23}avila  {c |}{col 31}{res}{space 2} 1.657244{col 43}{space 2} 1.130717{col 54}{space 1}    1.47{col 63}{space 3}0.143{col 71}{space 4}-.5640507{col 84}{space 3} 3.878538
{txt}{space 21}badajoz  {c |}{col 31}{res}{space 2}-.8627803{col 43}{space 2} 1.042291{col 54}{space 1}   -0.83{col 63}{space 3}0.408{col 71}{space 4}-2.910363{col 84}{space 3} 1.184803
{txt}{space 19}barcelona  {c |}{col 31}{res}{space 2} 1.177437{col 43}{space 2} 1.563954{col 54}{space 1}    0.75{col 63}{space 3}0.452{col 71}{space 4}-1.894954{col 84}{space 3} 4.249828
{txt}{space 22}burgos  {c |}{col 31}{res}{space 2} .6393479{col 43}{space 2} 1.061501{col 54}{space 1}    0.60{col 63}{space 3}0.547{col 71}{space 4}-1.445972{col 84}{space 3} 2.724668
{txt}{space 21}caceres  {c |}{col 31}{res}{space 2}-.1368107{col 43}{space 2} .9666821{col 54}{space 1}   -0.14{col 63}{space 3}0.888{col 71}{space 4}-2.035859{col 84}{space 3} 1.762238
{txt}{space 23}cadiz  {c |}{col 31}{res}{space 2}-2.654056{col 43}{space 2} 1.201115{col 54}{space 1}   -2.21{col 63}{space 3}0.028{col 71}{space 4}-5.013649{col 84}{space 3}-.2944638
{txt}{space 19}cantabria  {c |}{col 31}{res}{space 2}-.1821704{col 43}{space 2} 1.254447{col 54}{space 1}   -0.15{col 63}{space 3}0.885{col 71}{space 4}-2.646533{col 84}{space 3} 2.282192
{txt}{space 19}castellon  {c |}{col 31}{res}{space 2}-.3980957{col 43}{space 2} 1.199816{col 54}{space 1}   -0.33{col 63}{space 3}0.740{col 71}{space 4}-2.755136{col 84}{space 3} 1.958945
{txt}{space 17}ciudad real  {c |}{col 31}{res}{space 2} .0062107{col 43}{space 2} 1.128401{col 54}{space 1}    0.01{col 63}{space 3}0.996{col 71}{space 4}-2.210535{col 84}{space 3} 2.222957
{txt}{space 21}cordoba  {c |}{col 31}{res}{space 2}-.8580686{col 43}{space 2} 1.049799{col 54}{space 1}   -0.82{col 63}{space 3}0.414{col 71}{space 4}  -2.9204{col 84}{space 3} 1.204263
{txt}{space 22}cuenca  {c |}{col 31}{res}{space 2} .7867693{col 43}{space 2} 1.125618{col 54}{space 1}    0.70{col 63}{space 3}0.485{col 71}{space 4}-1.424509{col 84}{space 3} 2.998048
{txt}{space 20}gipuzkoa  {c |}{col 31}{res}{space 2} 1.669358{col 43}{space 2} 1.830834{col 54}{space 1}    0.91{col 63}{space 3}0.362{col 71}{space 4}-1.927319{col 84}{space 3} 5.266034
{txt}{space 22}girona  {c |}{col 31}{res}{space 2} 2.006043{col 43}{space 2} 1.691573{col 54}{space 1}    1.19{col 63}{space 3}0.236{col 71}{space 4}-1.317056{col 84}{space 3} 5.329141
{txt}{space 21}granada  {c |}{col 31}{res}{space 2}-.7194311{col 43}{space 2} .9910651{col 54}{space 1}   -0.73{col 63}{space 3}0.468{col 71}{space 4} -2.66638{col 84}{space 3} 1.227518
{txt}{space 17}guadalajara  {c |}{col 31}{res}{space 2}-.6798946{col 43}{space 2} 1.127901{col 54}{space 1}   -0.60{col 63}{space 3}0.547{col 71}{space 4}-2.895658{col 84}{space 3} 1.535869
{txt}{space 22}huelva  {c |}{col 31}{res}{space 2}-2.075689{col 43}{space 2} 1.213817{col 54}{space 1}   -1.71{col 63}{space 3}0.088{col 71}{space 4}-4.460233{col 84}{space 3} .3088559
{txt}{space 22}huesca  {c |}{col 31}{res}{space 2}-.2514295{col 43}{space 2} 1.184482{col 54}{space 1}   -0.21{col 63}{space 3}0.832{col 71}{space 4}-2.578346{col 84}{space 3} 2.075487
{txt}{space 14}islas baleares  {c |}{col 31}{res}{space 2}-.3859252{col 43}{space 2}  1.32418{col 54}{space 1}   -0.29{col 63}{space 3}0.771{col 71}{space 4}-2.987279{col 84}{space 3} 2.215428
{txt}{space 24}jaen  {c |}{col 31}{res}{space 2}-1.025346{col 43}{space 2} 1.053132{col 54}{space 1}   -0.97{col 63}{space 3}0.331{col 71}{space 4}-3.094225{col 84}{space 3} 1.043533
{txt}{space 20}la rioja  {c |}{col 31}{res}{space 2} .6026265{col 43}{space 2}   1.0069{col 54}{space 1}    0.60{col 63}{space 3}0.550{col 71}{space 4}-1.375431{col 84}{space 3} 2.580684
{txt}{space 18}las palmas  {c |}{col 31}{res}{space 2}-.7277695{col 43}{space 2} 1.534716{col 54}{space 1}   -0.47{col 63}{space 3}0.636{col 71}{space 4}-3.742722{col 84}{space 3} 2.287183
{txt}{space 24}leon  {c |}{col 31}{res}{space 2}-.0774143{col 43}{space 2} 1.098152{col 54}{space 1}   -0.07{col 63}{space 3}0.944{col 71}{space 4}-2.234736{col 84}{space 3} 2.079908
{txt}{space 22}lleida  {c |}{col 31}{res}{space 2} 2.681768{col 43}{space 2} 1.880595{col 54}{space 1}    1.43{col 63}{space 3}0.154{col 71}{space 4}-1.012664{col 84}{space 3} 6.376199
{txt}{space 24}lugo  {c |}{col 31}{res}{space 2} .7595969{col 43}{space 2} 1.250348{col 54}{space 1}    0.61{col 63}{space 3}0.544{col 71}{space 4}-1.696714{col 84}{space 3} 3.215908
{txt}{space 22}madrid  {c |}{col 31}{res}{space 2}-1.280917{col 43}{space 2} 1.295134{col 54}{space 1}   -0.99{col 63}{space 3}0.323{col 71}{space 4} -3.82521{col 84}{space 3} 1.263375
{txt}{space 22}malaga  {c |}{col 31}{res}{space 2}-2.372308{col 43}{space 2} 1.127494{col 54}{space 1}   -2.10{col 63}{space 3}0.036{col 71}{space 4}-4.587272{col 84}{space 3}-.1573454
{txt}{space 22}murcia  {c |}{col 31}{res}{space 2}-.4627658{col 43}{space 2} 1.546597{col 54}{space 1}   -0.30{col 63}{space 3}0.765{col 71}{space 4}-3.501058{col 84}{space 3} 2.575526
{txt}{space 21}navarra  {c |}{col 31}{res}{space 2} .6179125{col 43}{space 2} 1.590539{col 54}{space 1}    0.39{col 63}{space 3}0.698{col 71}{space 4}-2.506703{col 84}{space 3} 3.742528
{txt}{space 21}ourense  {c |}{col 31}{res}{space 2} 2.074914{col 43}{space 2} 1.467521{col 54}{space 1}    1.41{col 63}{space 3}0.158{col 71}{space 4} -.808033{col 84}{space 3}  4.95786
{txt}{space 20}palencia  {c |}{col 31}{res}{space 2} .9427454{col 43}{space 2}  1.01596{col 54}{space 1}    0.93{col 63}{space 3}0.354{col 71}{space 4}-1.053109{col 84}{space 3}   2.9386
{txt}{space 18}pontevedra  {c |}{col 31}{res}{space 2} .4700254{col 43}{space 2} 1.221833{col 54}{space 1}    0.38{col 63}{space 3}0.701{col 71}{space 4}-1.930267{col 84}{space 3} 2.870318
{txt}{space 19}salamanca  {c |}{col 31}{res}{space 2}  .076225{col 43}{space 2} 1.044482{col 54}{space 1}    0.07{col 63}{space 3}0.942{col 71}{space 4}-1.975662{col 84}{space 3} 2.128112
{txt}{space 6}santa cruz de tenerife  {c |}{col 31}{res}{space 2}-.0082565{col 43}{space 2} 1.117243{col 54}{space 1}   -0.01{col 63}{space 3}0.994{col 71}{space 4}-2.203082{col 84}{space 3} 2.186569
{txt}{space 21}segovia  {c |}{col 31}{res}{space 2} .9422681{col 43}{space 2} 1.150064{col 54}{space 1}    0.82{col 63}{space 3}0.413{col 71}{space 4}-1.317034{col 84}{space 3} 3.201571
{txt}{space 21}sevilla  {c |}{col 31}{res}{space 2}-1.582695{col 43}{space 2} 1.226851{col 54}{space 1}   -1.29{col 63}{space 3}0.198{col 71}{space 4}-3.992846{col 84}{space 3} .8274567
{txt}{space 23}soria  {c |}{col 31}{res}{space 2} 1.573875{col 43}{space 2} 1.739606{col 54}{space 1}    0.90{col 63}{space 3}0.366{col 71}{space 4}-1.843584{col 84}{space 3} 4.991333
{txt}{space 19}tarragona  {c |}{col 31}{res}{space 2} 1.008214{col 43}{space 2} 1.656345{col 54}{space 1}    0.61{col 63}{space 3}0.543{col 71}{space 4} -2.24568{col 84}{space 3} 4.262107
{txt}{space 22}teruel  {c |}{col 31}{res}{space 2}-.2033263{col 43}{space 2} 1.511456{col 54}{space 1}   -0.13{col 63}{space 3}0.893{col 71}{space 4}-3.172585{col 84}{space 3} 2.765932
{txt}{space 22}toledo  {c |}{col 31}{res}{space 2} -.503416{col 43}{space 2}  1.11236{col 54}{space 1}   -0.45{col 63}{space 3}0.651{col 71}{space 4}-2.688648{col 84}{space 3} 1.681816
{txt}{space 20}valencia  {c |}{col 31}{res}{space 2}-.2601511{col 43}{space 2} 1.300851{col 54}{space 1}   -0.20{col 63}{space 3}0.842{col 71}{space 4}-2.815675{col 84}{space 3} 2.295372
{txt}{space 18}valladolid  {c |}{col 31}{res}{space 2}-.2405698{col 43}{space 2} 1.058538{col 54}{space 1}   -0.23{col 63}{space 3}0.820{col 71}{space 4}-2.320069{col 84}{space 3} 1.838929
{txt}{space 21}vizcaya  {c |}{col 31}{res}{space 2} 1.915462{col 43}{space 2} 1.584578{col 54}{space 1}    1.21{col 63}{space 3}0.227{col 71}{space 4}-1.197445{col 84}{space 3} 5.028369
{txt}{space 22}zamora  {c |}{col 31}{res}{space 2} 1.051522{col 43}{space 2} 1.032349{col 54}{space 1}    1.02{col 63}{space 3}0.309{col 71}{space 4}-.9765288{col 84}{space 3} 3.079573
{txt}{space 20}zaragoza  {c |}{col 31}{res}{space 2}-1.398021{col 43}{space 2} 1.332279{col 54}{space 1}   -1.05{col 63}{space 3}0.295{col 71}{space 4}-4.015286{col 84}{space 3} 1.219243
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} 3.185121{col 43}{space 2}  3.00908{col 54}{space 1}    1.06{col 63}{space 3}0.290{col 71}{space 4}-2.726222{col 84}{space 3} 9.096463
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-1.7509378
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "All"

{txt}added macro:
           e(Election) : "{res:All}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_all_ex15: reg var_votes_inc_ours top_prizes_gdp_ours_c c.expenditure_gdp_ours_c##i.year $controls_ours i.province_num, robust, if year!=2015

{txt}Linear regression                               Number of obs     = {res}       550
                                                {txt}F(73, 476)        =  {res}    45.61
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8049
                                                {txt}Root MSE          =    {res} 2.9862

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}           var_votes_inc_ours{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}top_prizes_gdp_ours_c {c |}{col 31}{res}{space 2} .3605709{col 43}{space 2} .4039254{col 54}{space 1}    0.89{col 63}{space 3}0.372{col 71}{space 4}-.4331264{col 84}{space 3} 1.154268
{txt}{space 7}expenditure_gdp_ours_c {c |}{col 31}{res}{space 2}-10.64204{col 43}{space 2} 7.706093{col 54}{space 1}   -1.38{col 63}{space 3}0.168{col 71}{space 4}-25.78421{col 84}{space 3} 4.500126
{txt}{space 29} {c |}
{space 25}year {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} 3.696956{col 43}{space 2} 2.273546{col 54}{space 1}    1.63{col 63}{space 3}0.105{col 71}{space 4}-.7704711{col 84}{space 3} 8.164382
{txt}{space 24}1996  {c |}{col 31}{res}{space 2}-.1696163{col 43}{space 2} 1.976054{col 54}{space 1}   -0.09{col 63}{space 3}0.932{col 71}{space 4}-4.052484{col 84}{space 3} 3.713252
{txt}{space 24}2000  {c |}{col 31}{res}{space 2} 6.796963{col 43}{space 2} 2.288621{col 54}{space 1}    2.97{col 63}{space 3}0.003{col 71}{space 4} 2.299914{col 84}{space 3} 11.29401
{txt}{space 24}2004  {c |}{col 31}{res}{space 2}-8.559855{col 43}{space 2} 2.287399{col 54}{space 1}   -3.74{col 63}{space 3}0.000{col 71}{space 4} -13.0545{col 84}{space 3}-4.065207
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} 4.079484{col 43}{space 2} 2.718854{col 54}{space 1}    1.50{col 63}{space 3}0.134{col 71}{space 4}-1.262957{col 84}{space 3} 9.421925
{txt}{space 24}2011  {c |}{col 31}{res}{space 2}-15.68238{col 43}{space 2} 2.531485{col 54}{space 1}   -6.19{col 63}{space 3}0.000{col 71}{space 4}-20.65665{col 84}{space 3}-10.70811
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} .7726668{col 43}{space 2} 2.717041{col 54}{space 1}    0.28{col 63}{space 3}0.776{col 71}{space 4}-4.566212{col 84}{space 3} 6.111545
{txt}{space 24}2019  {c |}{col 31}{res}{space 2}-1.227245{col 43}{space 2} 2.664894{col 54}{space 1}   -0.46{col 63}{space 3}0.645{col 71}{space 4}-6.463655{col 84}{space 3} 4.009165
{txt}{space 24}2023  {c |}{col 31}{res}{space 2} 7.530622{col 43}{space 2} 2.259986{col 54}{space 1}    3.33{col 63}{space 3}0.001{col 71}{space 4} 3.089839{col 84}{space 3}  11.9714
{txt}{space 29} {c |}
year#c.expenditure_gdp_ours_c {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} 8.435501{col 43}{space 2} 7.681591{col 54}{space 1}    1.10{col 63}{space 3}0.273{col 71}{space 4} -6.65852{col 84}{space 3} 23.52952
{txt}{space 24}1996  {c |}{col 31}{res}{space 2} 6.825993{col 43}{space 2} 7.260396{col 54}{space 1}    0.94{col 63}{space 3}0.348{col 71}{space 4}-7.440396{col 84}{space 3} 21.09238
{txt}{space 24}2000  {c |}{col 31}{res}{space 2}-3.059861{col 43}{space 2} 7.339601{col 54}{space 1}   -0.42{col 63}{space 3}0.677{col 71}{space 4}-17.48189{col 84}{space 3} 11.36216
{txt}{space 24}2004  {c |}{col 31}{res}{space 2} 12.74526{col 43}{space 2} 7.497458{col 54}{space 1}    1.70{col 63}{space 3}0.090{col 71}{space 4}-1.986942{col 84}{space 3} 27.47747
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} 2.426624{col 43}{space 2} 8.414316{col 54}{space 1}    0.29{col 63}{space 3}0.773{col 71}{space 4}-14.10717{col 84}{space 3} 18.96042
{txt}{space 24}2011  {c |}{col 31}{res}{space 2} 12.43549{col 43}{space 2} 7.013149{col 54}{space 1}    1.77{col 63}{space 3}0.077{col 71}{space 4} -1.34507{col 84}{space 3} 26.21605
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} 10.38516{col 43}{space 2} 6.766045{col 54}{space 1}    1.53{col 63}{space 3}0.125{col 71}{space 4}-2.909844{col 84}{space 3} 23.68017
{txt}{space 24}2019  {c |}{col 31}{res}{space 2} 11.80219{col 43}{space 2} 6.933641{col 54}{space 1}    1.70{col 63}{space 3}0.089{col 71}{space 4}-1.822137{col 84}{space 3} 25.42652
{txt}{space 24}2023  {c |}{col 31}{res}{space 2}-8.169476{col 43}{space 2} 7.489241{col 54}{space 1}   -1.09{col 63}{space 3}0.276{col 71}{space 4}-22.88554{col 84}{space 3} 6.546585
{txt}{space 29} {c |}
{space 8}D_unemployment_rate_2 {c |}{col 31}{res}{space 2}-.1059937{col 43}{space 2} .0474695{col 54}{space 1}   -2.23{col 63}{space 3}0.026{col 71}{space 4}-.1992695{col 84}{space 3} -.012718
{txt}{space 19}D_gdp_pc_2 {c |}{col 31}{res}{space 2} .0173642{col 43}{space 2} .0193574{col 54}{space 1}    0.90{col 63}{space 3}0.370{col 71}{space 4}-.0206723{col 84}{space 3} .0554006
{txt}{space 22}D_cpi_2 {c |}{col 31}{res}{space 2} -.284307{col 43}{space 2} .1282124{col 54}{space 1}   -2.22{col 63}{space 3}0.027{col 71}{space 4}-.5362394{col 84}{space 3}-.0323746
{txt}{space 12}D_housing_price_2 {c |}{col 31}{res}{space 2} .0217175{col 43}{space 2}  .015231{col 54}{space 1}    1.43{col 63}{space 3}0.155{col 71}{space 4}-.0082109{col 84}{space 3} .0516458
{txt}{space 29} {c |}
{space 17}province_num {c |}
{space 23}alava  {c |}{col 31}{res}{space 2}-.2300765{col 43}{space 2}  1.68949{col 54}{space 1}   -0.14{col 63}{space 3}0.892{col 71}{space 4}-3.549856{col 84}{space 3} 3.089703
{txt}{space 20}albacete  {c |}{col 31}{res}{space 2}-.2720088{col 43}{space 2} 1.076859{col 54}{space 1}   -0.25{col 63}{space 3}0.801{col 71}{space 4}-2.387994{col 84}{space 3} 1.843976
{txt}{space 20}alicante  {c |}{col 31}{res}{space 2} .2755137{col 43}{space 2} 1.236525{col 54}{space 1}    0.22{col 63}{space 3}0.824{col 71}{space 4}-2.154208{col 84}{space 3} 2.705236
{txt}{space 21}almeria  {c |}{col 31}{res}{space 2}-1.125987{col 43}{space 2} 1.409716{col 54}{space 1}   -0.80{col 63}{space 3}0.425{col 71}{space 4}-3.896022{col 84}{space 3} 1.644049
{txt}{space 20}asturias  {c |}{col 31}{res}{space 2} .4517589{col 43}{space 2} 1.273355{col 54}{space 1}    0.35{col 63}{space 3}0.723{col 71}{space 4}-2.050332{col 84}{space 3}  2.95385
{txt}{space 23}avila  {c |}{col 31}{res}{space 2}  1.84707{col 43}{space 2} 1.217248{col 54}{space 1}    1.52{col 63}{space 3}0.130{col 71}{space 4} -.544775{col 84}{space 3} 4.238915
{txt}{space 21}badajoz  {c |}{col 31}{res}{space 2}-1.031702{col 43}{space 2} 1.167596{col 54}{space 1}   -0.88{col 63}{space 3}0.377{col 71}{space 4}-3.325981{col 84}{space 3} 1.262577
{txt}{space 19}barcelona  {c |}{col 31}{res}{space 2} .6304654{col 43}{space 2}  1.65788{col 54}{space 1}    0.38{col 63}{space 3}0.704{col 71}{space 4}-2.627202{col 84}{space 3} 3.888133
{txt}{space 22}burgos  {c |}{col 31}{res}{space 2} .6543252{col 43}{space 2} 1.166129{col 54}{space 1}    0.56{col 63}{space 3}0.575{col 71}{space 4}-1.637072{col 84}{space 3} 2.945723
{txt}{space 21}caceres  {c |}{col 31}{res}{space 2}-.0907994{col 43}{space 2} 1.059732{col 54}{space 1}   -0.09{col 63}{space 3}0.932{col 71}{space 4}-2.173131{col 84}{space 3} 1.991532
{txt}{space 23}cadiz  {c |}{col 31}{res}{space 2}-2.771401{col 43}{space 2} 1.310133{col 54}{space 1}   -2.12{col 63}{space 3}0.035{col 71}{space 4} -5.34576{col 84}{space 3}-.1970429
{txt}{space 19}cantabria  {c |}{col 31}{res}{space 2}-.3366733{col 43}{space 2} 1.374271{col 54}{space 1}   -0.24{col 63}{space 3}0.807{col 71}{space 4}-3.037061{col 84}{space 3} 2.363714
{txt}{space 19}castellon  {c |}{col 31}{res}{space 2} .0946072{col 43}{space 2} 1.189268{col 54}{space 1}    0.08{col 63}{space 3}0.937{col 71}{space 4}-2.242257{col 84}{space 3} 2.431471
{txt}{space 17}ciudad real  {c |}{col 31}{res}{space 2} .1090436{col 43}{space 2} 1.238632{col 54}{space 1}    0.09{col 63}{space 3}0.930{col 71}{space 4} -2.32482{col 84}{space 3} 2.542907
{txt}{space 21}cordoba  {c |}{col 31}{res}{space 2}-1.175978{col 43}{space 2}  1.14919{col 54}{space 1}   -1.02{col 63}{space 3}0.307{col 71}{space 4}-3.434092{col 84}{space 3} 1.082135
{txt}{space 22}cuenca  {c |}{col 31}{res}{space 2} .7939584{col 43}{space 2}  1.24115{col 54}{space 1}    0.64{col 63}{space 3}0.523{col 71}{space 4}-1.644851{col 84}{space 3} 3.232768
{txt}{space 20}gipuzkoa  {c |}{col 31}{res}{space 2} .6993581{col 43}{space 2} 1.811469{col 54}{space 1}    0.39{col 63}{space 3}0.700{col 71}{space 4}-2.860106{col 84}{space 3} 4.258822
{txt}{space 22}girona  {c |}{col 31}{res}{space 2} 1.410808{col 43}{space 2} 1.791218{col 54}{space 1}    0.79{col 63}{space 3}0.431{col 71}{space 4}-2.108865{col 84}{space 3} 4.930481
{txt}{space 21}granada  {c |}{col 31}{res}{space 2}-.8592701{col 43}{space 2} 1.080992{col 54}{space 1}   -0.79{col 63}{space 3}0.427{col 71}{space 4}-2.983377{col 84}{space 3} 1.264836
{txt}{space 17}guadalajara  {c |}{col 31}{res}{space 2}-.5276885{col 43}{space 2} 1.205062{col 54}{space 1}   -0.44{col 63}{space 3}0.662{col 71}{space 4}-2.895588{col 84}{space 3} 1.840211
{txt}{space 22}huelva  {c |}{col 31}{res}{space 2} -2.49884{col 43}{space 2} 1.330751{col 54}{space 1}   -1.88{col 63}{space 3}0.061{col 71}{space 4}-5.113712{col 84}{space 3} .1160325
{txt}{space 22}huesca  {c |}{col 31}{res}{space 2}-.2948792{col 43}{space 2} 1.290132{col 54}{space 1}   -0.23{col 63}{space 3}0.819{col 71}{space 4}-2.829937{col 84}{space 3} 2.240178
{txt}{space 14}islas baleares  {c |}{col 31}{res}{space 2}-.0345186{col 43}{space 2} 1.341866{col 54}{space 1}   -0.03{col 63}{space 3}0.979{col 71}{space 4}-2.671232{col 84}{space 3} 2.602195
{txt}{space 24}jaen  {c |}{col 31}{res}{space 2}-1.395675{col 43}{space 2} 1.148182{col 54}{space 1}   -1.22{col 63}{space 3}0.225{col 71}{space 4}-3.651808{col 84}{space 3} .8604578
{txt}{space 20}la rioja  {c |}{col 31}{res}{space 2} .7112523{col 43}{space 2} 1.111356{col 54}{space 1}    0.64{col 63}{space 3}0.522{col 71}{space 4}-1.472519{col 84}{space 3} 2.895023
{txt}{space 18}las palmas  {c |}{col 31}{res}{space 2}-.2655595{col 43}{space 2}  1.52707{col 54}{space 1}   -0.17{col 63}{space 3}0.862{col 71}{space 4}-3.266191{col 84}{space 3} 2.735072
{txt}{space 24}leon  {c |}{col 31}{res}{space 2}-.0442972{col 43}{space 2} 1.197299{col 54}{space 1}   -0.04{col 63}{space 3}0.971{col 71}{space 4}-2.396941{col 84}{space 3} 2.308347
{txt}{space 22}lleida  {c |}{col 31}{res}{space 2} 2.338046{col 43}{space 2} 1.968446{col 54}{space 1}    1.19{col 63}{space 3}0.236{col 71}{space 4}-1.529872{col 84}{space 3} 6.205963
{txt}{space 24}lugo  {c |}{col 31}{res}{space 2}  .547407{col 43}{space 2} 1.372558{col 54}{space 1}    0.40{col 63}{space 3}0.690{col 71}{space 4}-2.149615{col 84}{space 3} 3.244429
{txt}{space 22}madrid  {c |}{col 31}{res}{space 2}-1.216212{col 43}{space 2} 1.418019{col 54}{space 1}   -0.86{col 63}{space 3}0.391{col 71}{space 4}-4.002562{col 84}{space 3} 1.570138
{txt}{space 22}malaga  {c |}{col 31}{res}{space 2}-2.192003{col 43}{space 2} 1.189177{col 54}{space 1}   -1.84{col 63}{space 3}0.066{col 71}{space 4}-4.528688{col 84}{space 3}  .144683
{txt}{space 22}murcia  {c |}{col 31}{res}{space 2} .2314609{col 43}{space 2} 1.462988{col 54}{space 1}    0.16{col 63}{space 3}0.874{col 71}{space 4}-2.643252{col 84}{space 3} 3.106174
{txt}{space 21}navarra  {c |}{col 31}{res}{space 2}  -.01093{col 43}{space 2} 1.660245{col 54}{space 1}   -0.01{col 63}{space 3}0.995{col 71}{space 4}-3.273245{col 84}{space 3} 3.251385
{txt}{space 21}ourense  {c |}{col 31}{res}{space 2} 1.845523{col 43}{space 2} 1.597379{col 54}{space 1}    1.16{col 63}{space 3}0.249{col 71}{space 4}-1.293264{col 84}{space 3}  4.98431
{txt}{space 20}palencia  {c |}{col 31}{res}{space 2} .8587538{col 43}{space 2} 1.119537{col 54}{space 1}    0.77{col 63}{space 3}0.443{col 71}{space 4}-1.341091{col 84}{space 3} 3.058599
{txt}{space 18}pontevedra  {c |}{col 31}{res}{space 2} .5282995{col 43}{space 2} 1.339425{col 54}{space 1}    0.39{col 63}{space 3}0.693{col 71}{space 4}-2.103617{col 84}{space 3} 3.160216
{txt}{space 19}salamanca  {c |}{col 31}{res}{space 2} .1596348{col 43}{space 2} 1.145025{col 54}{space 1}    0.14{col 63}{space 3}0.889{col 71}{space 4}-2.090293{col 84}{space 3} 2.409563
{txt}{space 6}santa cruz de tenerife  {c |}{col 31}{res}{space 2}-.0290106{col 43}{space 2} 1.212026{col 54}{space 1}   -0.02{col 63}{space 3}0.981{col 71}{space 4}-2.410593{col 84}{space 3} 2.352572
{txt}{space 21}segovia  {c |}{col 31}{res}{space 2} 1.137399{col 43}{space 2} 1.243732{col 54}{space 1}    0.91{col 63}{space 3}0.361{col 71}{space 4}-1.306485{col 84}{space 3} 3.581283
{txt}{space 21}sevilla  {c |}{col 31}{res}{space 2}-2.105029{col 43}{space 2} 1.309192{col 54}{space 1}   -1.61{col 63}{space 3}0.109{col 71}{space 4}-4.677539{col 84}{space 3} .4674818
{txt}{space 23}soria  {c |}{col 31}{res}{space 2} 1.781072{col 43}{space 2} 1.808618{col 54}{space 1}    0.98{col 63}{space 3}0.325{col 71}{space 4} -1.77279{col 84}{space 3} 5.334935
{txt}{space 19}tarragona  {c |}{col 31}{res}{space 2} .6017708{col 43}{space 2} 1.831474{col 54}{space 1}    0.33{col 63}{space 3}0.743{col 71}{space 4}-2.997003{col 84}{space 3} 4.200545
{txt}{space 22}teruel  {c |}{col 31}{res}{space 2} -.277643{col 43}{space 2} 1.663047{col 54}{space 1}   -0.17{col 63}{space 3}0.867{col 71}{space 4}-3.545465{col 84}{space 3} 2.990179
{txt}{space 22}toledo  {c |}{col 31}{res}{space 2}-.3495671{col 43}{space 2} 1.197081{col 54}{space 1}   -0.29{col 63}{space 3}0.770{col 71}{space 4}-2.701783{col 84}{space 3} 2.002649
{txt}{space 20}valencia  {c |}{col 31}{res}{space 2} .2675219{col 43}{space 2}  1.27381{col 54}{space 1}    0.21{col 63}{space 3}0.834{col 71}{space 4}-2.235464{col 84}{space 3} 2.770508
{txt}{space 18}valladolid  {c |}{col 31}{res}{space 2}-.3545534{col 43}{space 2}  1.18091{col 54}{space 1}   -0.30{col 63}{space 3}0.764{col 71}{space 4}-2.674995{col 84}{space 3} 1.965888
{txt}{space 21}vizcaya  {c |}{col 31}{res}{space 2} 1.155199{col 43}{space 2} 1.547264{col 54}{space 1}    0.75{col 63}{space 3}0.456{col 71}{space 4}-1.885114{col 84}{space 3} 4.195512
{txt}{space 22}zamora  {c |}{col 31}{res}{space 2} 1.064356{col 43}{space 2}  1.13614{col 54}{space 1}    0.94{col 63}{space 3}0.349{col 71}{space 4}-1.168115{col 84}{space 3} 3.296826
{txt}{space 20}zaragoza  {c |}{col 31}{res}{space 2}-1.483995{col 43}{space 2} 1.469203{col 54}{space 1}   -1.01{col 63}{space 3}0.313{col 71}{space 4}-4.370919{col 84}{space 3}  1.40293
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} 3.712331{col 43}{space 2} 3.114977{col 54}{space 1}    1.19{col 63}{space 3}0.234{col 71}{space 4}-2.408474{col 84}{space 3} 9.833137
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-.53635061
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "All"

{txt}added macro:
           e(Election) : "{res:All}"

{com}. estadd local Pop_weights "$\times$"

{txt}added macro:
        e(Pop_weights) : "{res:$\times$}"

{com}. 
. eststo col_4_meta: reg var_votes_inc_ours var_votes_inc_ours

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       600
{txt}{hline 13}{c +}{hline 34}   F(1, 598)       = {res}        .
{txt}       Model {c |} {res} 32423.3892         1  32423.3892   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res}          0       598           0   {txt}R-squared       ={res}    1.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    1.0000
{txt}       Total {c |} {res} 32423.3892       599  54.1291974   {txt}Root MSE        =   {res}      0

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}var_votes_inc_ours{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var_votes_inc_ours {c |}{col 20}{res}{space 2}        1{col 32}{space 2}        .{col 43}{space 1}       .{col 52}{space 3}    .{col 60}{space 4}        .{col 73}{space 3}        .
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 4.44e-16{col 32}{space 2}        .{col 43}{space 1}       .{col 52}{space 3}    .{col 60}{space 4}        .{col 73}{space 3}        .
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-1.7509378
{txt}
{com}. estadd local Estimation "Meta"

{txt}added macro:
         e(Estimation) : "{res:Meta}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year ""

{txt}added macro:
               e(Year) : "{res:}"

{com}. estadd local Province ""

{txt}added macro:
           e(Province) : "{res:}"

{com}. estadd local Cluster ""

{txt}added macro:
            e(Cluster) : "{res:}"

{com}. estadd local Controls ""

{txt}added macro:
           e(Controls) : "{res:}"

{com}. estadd local Election "All"

{txt}added macro:
           e(Election) : "{res:All}"

{com}. estadd local Pop_weights ""

{txt}added macro:
        e(Pop_weights) : "{res:}"

{com}. 
. * Table A10 - Electoral Results (Defining Prizes based on the Latest Lottery) without Population Weights, by Election, Using Our Data
. esttab col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 col_4_all col_4_meta using ${c -(}tables{c )-}electoral_results_our_data_by_election_inter_y.tex, ///
>                 keep(top_prizes_gdp_ours_c)  ///
>                 nocon r2 ///
>                 mtitles se mtitles("Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." ///
>                                                         "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." ///
>                                                         "Vote Incumb.")  ///
>                 coeflabels(top_prizes_gdp_ours_c "Prev. Year Top Prizes")  ///
>                                         scalars("MeanDV Outcome Mean" "Estimation Estimation" "Data Data" "Year Year FEs" "Province Province FEs" "Controls Controls" "Cluster Cluster Province" "Election Election" "Pop_weights Pop. Weights")  ///
>         star(* 0.05 ** 0.01) b(%9.3f) replace
{res}{txt}(note: file Results/Tables_Electoral/electoral_results_our_data_by_election_inter_y.tex not found)
(output written to {browse  `"Results/Tables_Electoral/electoral_results_our_data_by_election_inter_y.tex"'})

{com}.                 
. 
. **----------------------------------------------------------------------------**
. *** META ANALYSIS (WITHOUT POPULATION WEIGHTS)
. **----------------------------------------------------------------------------**
. 
. * Full period
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_ours_c]
{txt}  4{com}.     local se = _se[top_prizes_gdp_ours_c]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_89:col_4_89} are active now)
(results {stata estimates replay col_4_93:col_4_93} are active now)
(results {stata estimates replay col_4_96:col_4_96} are active now)
(results {stata estimates replay col_4_00:col_4_00} are active now)
(results {stata estimates replay col_4_04:col_4_04} are active now)
(results {stata estimates replay col_4_08:col_4_08} are active now)
(results {stata estimates replay col_4_11:col_4_11} are active now)
(results {stata estimates replay col_4_15:col_4_15} are active now)
(results {stata estimates replay col_4_16:col_4_16} are active now)
(results {stata estimates replay col_4_19_4:col_4_19_4} are active now)
(results {stata estimates replay col_4_19_11:col_4_19_11} are active now)
(results {stata estimates replay col_4_23:col_4_23} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient
{res}{txt}
{com}. rename c2 stderr
{res}{txt}
{com}. 
. gen regression = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
variable {bf}regression{sf} was {bf}{res}str8{sf}{txt} now {bf}{res}str10{sf}
{txt}(1 real change made)
variable {bf}regression{sf} was {bf}{res}str10{sf}{txt} now {bf}{res}str11{sf}
{txt}(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient stderr , studylabel(regression)
{txt}(638 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}12
{col 8}{txt}Study label:  {res}regression
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient
{txt}{col 11}Std. Err.:  {res}stderr
{txt}{col 9}Study label:  {res}regression

{txt}Meta-analysis summary{col 43}Number of studies = {res}    12
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 1.5817
{txt}{col 53}I2 (%) = {res}  83.40
{txt}{col 57}H2 = {res}   6.03

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_89{col 19}{c |}{res}{space 6}   -3.061{col 35}{space 3}   -4.762{col 47}{space 3}   -1.360{col 59}{space 5} 9.30
{col 1}{txt}         col_4_93{col 19}{c |}{res}{space 6}   -1.146{col 35}{space 3}   -3.059{col 47}{space 3}    0.767{col 59}{space 5} 8.57
{col 1}{txt}         col_4_96{col 19}{c |}{res}{space 6}    1.636{col 35}{space 3}    0.366{col 47}{space 3}    2.906{col 59}{space 5}10.85
{col 1}{txt}         col_4_00{col 19}{c |}{res}{space 6}    2.002{col 35}{space 3}    0.176{col 47}{space 3}    3.828{col 59}{space 5} 8.86
{col 1}{txt}         col_4_04{col 19}{c |}{res}{space 6}   -0.518{col 35}{space 3}   -2.100{col 47}{space 3}    1.063{col 59}{space 5} 9.72
{col 1}{txt}         col_4_08{col 19}{c |}{res}{space 6}    1.186{col 35}{space 3}   -0.543{col 47}{space 3}    2.916{col 59}{space 5} 9.20
{col 1}{txt}         col_4_11{col 19}{c |}{res}{space 6}   -0.200{col 35}{space 3}   -5.665{col 47}{space 3}    5.264{col 59}{space 5} 2.32
{col 1}{txt}         col_4_15{col 19}{c |}{res}{space 6}  -19.398{col 35}{space 3}  -29.974{col 47}{space 3}   -8.821{col 59}{space 5} 0.71
{col 1}{txt}         col_4_16{col 19}{c |}{res}{space 6}    0.200{col 35}{space 3}   -0.103{col 47}{space 3}    0.503{col 59}{space 5}13.52
{col 1}{txt}       col_4_19_4{col 19}{c |}{res}{space 6}   -0.103{col 35}{space 3}   -0.696{col 47}{space 3}    0.490{col 59}{space 5}12.97
{col 1}{txt}      col_4_19_11{col 19}{c |}{res}{space 6}    0.008{col 35}{space 3}   -1.234{col 47}{space 3}    1.250{col 59}{space 5}10.95
{col 1}{txt}         col_4_23{col 19}{c |}{res}{space 6}   -1.902{col 35}{space 3}   -6.531{col 47}{space 3}    2.727{col 59}{space 5} 3.03
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}   -0.154{col 35}{space 3}   -1.067{col 47}{space 3}    0.759
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}-0.33{txt}{col 50}Prob > |z| = {res}0.7409
{txt}Test of homogeneity: Q = chi2({res}11{txt}) = {res}41.43{txt}{col 52}Prob > Q = {res}0.0000
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient
{txt}{col 11}Std. Err.:  {res}stderr
{txt}{col 9}Study label:  {res}regression

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_our_noweights.png", replace  
{txt}(file Results/Figures_Electoral/forestplot_our_noweights.png written in PNG format)

{com}.                 
. 
. * Replication period
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_ours_c]
{txt}  4{com}.     local se = _se[top_prizes_gdp_ours_c]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_89:col_4_89} are active now)
(results {stata estimates replay col_4_93:col_4_93} are active now)
(results {stata estimates replay col_4_96:col_4_96} are active now)
(results {stata estimates replay col_4_00:col_4_00} are active now)
(results {stata estimates replay col_4_04:col_4_04} are active now)
(results {stata estimates replay col_4_08:col_4_08} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient_pre
{res}{txt}
{com}. rename c2 stderr_pre
{res}{txt}
{com}. 
. gen regression_pre = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression_pre = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression_pre{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient_pre stderr_pre , studylabel(regression_pre)
{txt}(644 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}6
{col 8}{txt}Study label:  {res}regression_pre
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient_pre

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr_pre
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_pre
{txt}{col 11}Std. Err.:  {res}stderr_pre
{txt}{col 9}Study label:  {res}regression_pre

{txt}Meta-analysis summary{col 43}Number of studies = {res}     6
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 3.0642
{txt}{col 53}I2 (%) = {res}  81.40
{txt}{col 57}H2 = {res}   5.38

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_89{col 19}{c |}{res}{space 6}   -3.061{col 35}{space 3}   -4.762{col 47}{space 3}   -1.360{col 59}{space 5}16.56
{col 1}{txt}         col_4_93{col 19}{c |}{res}{space 6}   -1.146{col 35}{space 3}   -3.059{col 47}{space 3}    0.767{col 59}{space 5}15.74
{col 1}{txt}         col_4_96{col 19}{c |}{res}{space 6}    1.636{col 35}{space 3}    0.366{col 47}{space 3}    2.906{col 59}{space 5}18.15
{col 1}{txt}         col_4_00{col 19}{c |}{res}{space 6}    2.002{col 35}{space 3}    0.176{col 47}{space 3}    3.828{col 59}{space 5}16.08
{col 1}{txt}         col_4_04{col 19}{c |}{res}{space 6}   -0.518{col 35}{space 3}   -2.100{col 47}{space 3}    1.063{col 59}{space 5}17.02
{col 1}{txt}         col_4_08{col 19}{c |}{res}{space 6}    1.186{col 35}{space 3}   -0.543{col 47}{space 3}    2.916{col 59}{space 5}16.45
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}    0.038{col 35}{space 3}   -1.520{col 47}{space 3}    1.597
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}0.05{txt}{col 50}Prob > |z| = {res}0.9614
{txt}Test of homogeneity: Q = chi2({res}5{txt}) = {res}26.72{txt}{col 52}Prob > Q = {res}0.0001
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_pre
{txt}{col 11}Std. Err.:  {res}stderr_pre
{txt}{col 9}Study label:  {res}regression_pre

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_pre_noweights.png", replace          
{txt}(file Results/Figures_Electoral/forestplot_pre_noweights.png written in PNG format)

{com}. 
. * Out-of-sample period
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_ours_c]
{txt}  4{com}.     local se = _se[top_prizes_gdp_ours_c]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_11:col_4_11} are active now)
(results {stata estimates replay col_4_15:col_4_15} are active now)
(results {stata estimates replay col_4_16:col_4_16} are active now)
(results {stata estimates replay col_4_19_4:col_4_19_4} are active now)
(results {stata estimates replay col_4_19_11:col_4_19_11} are active now)
(results {stata estimates replay col_4_23:col_4_23} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient_post
{res}{txt}
{com}. rename c2 stderr_post
{res}{txt}
{com}. 
. gen regression_post = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression_post = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression_post{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
variable {bf}regression_post{sf} was {bf}{res}str8{sf}{txt} now {bf}{res}str10{sf}
{txt}(1 real change made)
variable {bf}regression_post{sf} was {bf}{res}str10{sf}{txt} now {bf}{res}str11{sf}
{txt}(1 real change made)

{com}. 
. meta set coefficient_post stderr_post , studylabel(regression_post)
{txt}(644 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}6
{col 8}{txt}Study label:  {res}regression_post
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient_post

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr_post
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_post
{txt}{col 11}Std. Err.:  {res}stderr_post
{txt}{col 9}Study label:  {res}regression_post

{txt}Meta-analysis summary{col 43}Number of studies = {res}     6
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 0.0000
{txt}{col 53}I2 (%) = {res}   0.00
{txt}{col 57}H2 = {res}   1.00

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_11{col 19}{c |}{res}{space 6}   -0.200{col 35}{space 3}   -5.665{col 47}{space 3}    5.264{col 59}{space 5} 0.23
{col 1}{txt}         col_4_15{col 19}{c |}{res}{space 6}  -19.398{col 35}{space 3}  -29.974{col 47}{space 3}   -8.821{col 59}{space 5} 0.06
{col 1}{txt}         col_4_16{col 19}{c |}{res}{space 6}    0.200{col 35}{space 3}   -0.103{col 47}{space 3}    0.503{col 59}{space 5}75.29
{col 1}{txt}       col_4_19_4{col 19}{c |}{res}{space 6}   -0.103{col 35}{space 3}   -0.696{col 47}{space 3}    0.490{col 59}{space 5}19.61
{col 1}{txt}      col_4_19_11{col 19}{c |}{res}{space 6}    0.008{col 35}{space 3}   -1.234{col 47}{space 3}    1.250{col 59}{space 5} 4.48
{col 1}                0{col 19}{txt}{c |}{res}{space 6}   -1.902{col 35}{space 3}   -6.531{col 47}{space 3}    2.727{col 59}{space 5} 0.32
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}    0.112{col 35}{space 3}   -0.151{col 47}{space 3}    0.375
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}0.84{txt}{col 50}Prob > |z| = {res}0.4028
{txt}Test of homogeneity: Q = chi2({res}5{txt}) = {res}14.67{txt}{col 52}Prob > Q = {res}0.0119
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_post
{txt}{col 11}Std. Err.:  {res}stderr_post
{txt}{col 9}Study label:  {res}regression_post

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_post_noweights.png", replace         
{txt}(file Results/Figures_Electoral/forestplot_post_noweights.png written in PNG format)

{com}.                 
.                 
. restore
{txt}
{com}. 
. 
. **----------------------------------------------------------------------------**
. *** OUR DATA (WITH POPULATION WEIGHTS), ONLY SAME YEAR'S PRIZES AND EXPENDITURE
. **----------------------------------------------------------------------------**
. preserve
{txt}
{com}. 
. 
. global controls_ours D_unemployment_rate_2 D_gdp_pc_2 D_cpi_2 D_housing_price_2
{txt}
{com}. replace D_housing_price_2=housing_price_growth_term_1 if D_housing_price_==.
{txt}(100 real changes made)

{com}. 
. eststo col_4_89: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==1989
{txt}(sum of wgt is 38,358,555)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}    17.14
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.4921
                                                {txt}Root MSE          =    {res} 1.9305

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-2.483196{col 36}{space 2} .8431032{col 47}{space 1}   -2.95{col 56}{space 3}0.005{col 64}{space 4}-4.183475{col 77}{space 3} -.782916
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2}-4.576142{col 36}{space 2} 6.133394{col 47}{space 1}   -0.75{col 56}{space 3}0.460{col 64}{space 4}-16.94531{col 77}{space 3} 7.793025
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}  .183164{col 36}{space 2} .1386377{col 47}{space 1}    1.32{col 56}{space 3}0.193{col 64}{space 4}-.0964255{col 77}{space 3} .4627535
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}  .105065{col 36}{space 2} .0608837{col 47}{space 1}    1.73{col 56}{space 3}0.092{col 64}{space 4}-.0177187{col 77}{space 3} .2278487
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.5243641{col 36}{space 2} .2111884{col 47}{space 1}   -2.48{col 56}{space 3}0.017{col 64}{space 4}-.9502661{col 77}{space 3} -.098462
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0879506{col 36}{space 2} .0438549{col 47}{space 1}   -2.01{col 56}{space 3}0.051{col 64}{space 4}-.1763924{col 77}{space 3} .0004912
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 8.492945{col 36}{space 2} 3.810572{col 47}{space 1}    2.23{col 56}{space 3}0.031{col 64}{space 4} .8081934{col 77}{space 3}  16.1777
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-4.0485859
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1989"

{txt}added macro:
           e(Election) : "{res:1989}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_93: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==1993
{txt}(sum of wgt is 38,745,485)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.66
                                                {txt}Prob > F          = {res}    0.0279
                                                {txt}R-squared         = {res}    0.2502
                                                {txt}Root MSE          =    {res} 2.5202

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-1.814644{col 36}{space 2}  1.23473{col 47}{space 1}   -1.47{col 56}{space 3}0.149{col 64}{space 4}-4.304714{col 77}{space 3} .6754264
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} 9.565082{col 36}{space 2} 7.135402{col 47}{space 1}    1.34{col 56}{space 3}0.187{col 64}{space 4}-4.824827{col 77}{space 3} 23.95499
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.4400715{col 36}{space 2} .1574957{col 47}{space 1}   -2.79{col 56}{space 3}0.008{col 64}{space 4}-.7576919{col 77}{space 3}-.1224511
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}  .100655{col 36}{space 2} .0756826{col 47}{space 1}    1.33{col 56}{space 3}0.191{col 64}{space 4}-.0519735{col 77}{space 3} .2532836
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .0197916{col 36}{space 2} .0845624{col 47}{space 1}    0.23{col 56}{space 3}0.816{col 64}{space 4}-.1507447{col 77}{space 3} .1903279
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .1790415{col 36}{space 2} .1140773{col 47}{space 1}    1.57{col 56}{space 3}0.124{col 64}{space 4}-.0510173{col 77}{space 3} .4091004
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} -1.94483{col 36}{space 2} 2.984282{col 47}{space 1}   -0.65{col 56}{space 3}0.518{col 64}{space 4}-7.963209{col 77}{space 3} 4.073549
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-.81496548
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1993"

{txt}added macro:
           e(Election) : "{res:1993}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_96: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==1996
{txt}(sum of wgt is 40,095,757)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     3.71
                                                {txt}Prob > F          = {res}    0.0047
                                                {txt}R-squared         = {res}    0.3434
                                                {txt}Root MSE          =    {res} 2.7971

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} 2.154841{col 36}{space 2} 1.351386{col 47}{space 1}    1.59{col 56}{space 3}0.118{col 64}{space 4}-.5704887{col 77}{space 3}  4.88017
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} 2.748179{col 36}{space 2} 5.777633{col 47}{space 1}    0.48{col 56}{space 3}0.637{col 64}{space 4}-8.903529{col 77}{space 3} 14.39989
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0199547{col 36}{space 2}  .123912{col 47}{space 1}    0.16{col 56}{space 3}0.873{col 64}{space 4}-.2299376{col 77}{space 3} .2698469
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .1145873{col 36}{space 2} .0924556{col 47}{space 1}    1.24{col 56}{space 3}0.222{col 64}{space 4}-.0718671{col 77}{space 3} .3010417
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .1424535{col 36}{space 2} .3986949{col 47}{space 1}    0.36{col 56}{space 3}0.723{col 64}{space 4}-.6615914{col 77}{space 3} .9464984
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}  .477008{col 36}{space 2} .1232355{col 47}{space 1}    3.87{col 56}{space 3}0.000{col 64}{space 4} .2284799{col 77}{space 3} .7255361
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-3.263874{col 36}{space 2} 6.019763{col 47}{space 1}   -0.54{col 56}{space 3}0.590{col 64}{space 4}-15.40388{col 77}{space 3} 8.876134
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-1.1695254
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "1996"

{txt}added macro:
           e(Election) : "{res:1996}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_00: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==2000
{txt}(sum of wgt is 39,720,426)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     1.60
                                                {txt}Prob > F          = {res}    0.1717
                                                {txt}R-squared         = {res}    0.1349
                                                {txt}Root MSE          =    {res} 2.5065

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} 1.894487{col 36}{space 2} .9692749{col 47}{space 1}    1.95{col 56}{space 3}0.057{col 64}{space 4}-.0602419{col 77}{space 3} 3.849216
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2}-4.254908{col 36}{space 2} 6.855455{col 47}{space 1}   -0.62{col 56}{space 3}0.538{col 64}{space 4}-18.08025{col 77}{space 3} 9.570434
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.0599708{col 36}{space 2}  .158723{col 47}{space 1}   -0.38{col 56}{space 3}0.707{col 64}{space 4}-.3800662{col 77}{space 3} .2601247
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0006511{col 36}{space 2} .0295029{col 47}{space 1}    0.02{col 56}{space 3}0.982{col 64}{space 4}-.0588473{col 77}{space 3} .0601494
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .2940613{col 36}{space 2} .3445314{col 47}{space 1}    0.85{col 56}{space 3}0.398{col 64}{space 4}-.4007525{col 77}{space 3}  .988875
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0311154{col 36}{space 2} .0381161{col 47}{space 1}    0.82{col 56}{space 3}0.419{col 64}{space 4}-.0457531{col 77}{space 3} .1079838
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 2.670454{col 36}{space 2} 3.564534{col 47}{space 1}    0.75{col 56}{space 3}0.458{col 64}{space 4}-4.518113{col 77}{space 3} 9.859022
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}5.3671864
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2000"

{txt}added macro:
           e(Election) : "{res:2000}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_04: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==2004
{txt}(sum of wgt is 42,573,670)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.33
                                                {txt}Prob > F          = {res}    0.0488
                                                {txt}R-squared         = {res}    0.1512
                                                {txt}Root MSE          =    {res} 2.2264

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-.4591701{col 36}{space 2} 1.141505{col 47}{space 1}   -0.40{col 56}{space 3}0.689{col 64}{space 4}-2.761234{col 77}{space 3} 1.842894
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} 10.37446{col 36}{space 2} 3.988401{col 47}{space 1}    2.60{col 56}{space 3}0.013{col 64}{space 4} 2.331081{col 77}{space 3} 18.41783
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.0593802{col 36}{space 2} .1046827{col 47}{space 1}   -0.57{col 56}{space 3}0.574{col 64}{space 4}-.2704929{col 77}{space 3} .1517326
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0123729{col 36}{space 2} .0549153{col 47}{space 1}    0.23{col 56}{space 3}0.823{col 64}{space 4}-.0983745{col 77}{space 3} .1231202
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.1790912{col 36}{space 2} .3551736{col 47}{space 1}   -0.50{col 56}{space 3}0.617{col 64}{space 4} -.895367{col 77}{space 3} .5371846
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0049076{col 36}{space 2} .0155837{col 47}{space 1}   -0.31{col 56}{space 3}0.754{col 64}{space 4}-.0363352{col 77}{space 3} .0265199
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-7.161242{col 36}{space 2} 5.011889{col 47}{space 1}   -1.43{col 56}{space 3}0.160{col 64}{space 4}-17.26868{col 77}{space 3} 2.946196
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-6.6068785
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2004"

{txt}added macro:
           e(Election) : "{res:2004}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_08: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==2008
{txt}(sum of wgt is 45,054,694)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     3.48
                                                {txt}Prob > F          = {res}    0.0068
                                                {txt}R-squared         = {res}    0.1451
                                                {txt}Root MSE          =    {res} 4.5217

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} 1.895966{col 36}{space 2} 1.068691{col 47}{space 1}    1.77{col 56}{space 3}0.083{col 64}{space 4}-.2592544{col 77}{space 3} 4.051187
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2}-7.733733{col 36}{space 2} 8.737593{col 47}{space 1}   -0.89{col 56}{space 3}0.381{col 64}{space 4}-25.35477{col 77}{space 3} 9.887303
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.2932909{col 36}{space 2}  .182118{col 47}{space 1}   -1.61{col 56}{space 3}0.115{col 64}{space 4}-.6605669{col 77}{space 3} .0739851
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} -.110268{col 36}{space 2} .1599027{col 47}{space 1}   -0.69{col 56}{space 3}0.494{col 64}{space 4}-.4327426{col 77}{space 3} .2122066
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} .9392951{col 36}{space 2} .7370238{col 47}{space 1}    1.27{col 56}{space 3}0.209{col 64}{space 4}-.5470551{col 77}{space 3} 2.425645
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0347622{col 36}{space 2} .1327145{col 47}{space 1}    0.26{col 56}{space 3}0.795{col 64}{space 4}-.2328821{col 77}{space 3} .3024066
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-7.858184{col 36}{space 2} 12.56649{col 47}{space 1}   -0.63{col 56}{space 3}0.535{col 64}{space 4}-33.20093{col 77}{space 3} 17.48456
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}1.3883849
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2008"

{txt}added macro:
           e(Election) : "{res:2008}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_11: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==2011
{txt}(sum of wgt is 46,864,418)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     1.82
                                                {txt}Prob > F          = {res}    0.1185
                                                {txt}R-squared         = {res}    0.3420
                                                {txt}Root MSE          =    {res}  1.937

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-5.702983{col 36}{space 2} 3.838612{col 47}{space 1}   -1.49{col 56}{space 3}0.145{col 64}{space 4}-13.44428{col 77}{space 3} 2.038317
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2}  9.97794{col 36}{space 2} 4.090568{col 47}{space 1}    2.44{col 56}{space 3}0.019{col 64}{space 4} 1.728523{col 77}{space 3} 18.22736
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} -.017662{col 36}{space 2}  .152985{col 47}{space 1}   -0.12{col 56}{space 3}0.909{col 64}{space 4}-.3261857{col 77}{space 3} .2908617
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.1156051{col 36}{space 2} .0961055{col 47}{space 1}   -1.20{col 56}{space 3}0.236{col 64}{space 4}-.3094204{col 77}{space 3} .0782102
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.6196343{col 36}{space 2} .4068743{col 47}{space 1}   -1.52{col 56}{space 3}0.135{col 64}{space 4}-1.440175{col 77}{space 3} .2009059
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0646756{col 36}{space 2} .0479021{col 47}{space 1}    1.35{col 56}{space 3}0.184{col 64}{space 4}-.0319282{col 77}{space 3} .1612793
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-12.87118{col 36}{space 2} 2.977494{col 47}{space 1}   -4.32{col 56}{space 3}0.000{col 64}{space 4}-18.87587{col 77}{space 3}-6.866488
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-15.269305
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2011"

{txt}added macro:
           e(Election) : "{res:2011}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_15: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==2015
{txt}(sum of wgt is 46,607,325)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     7.95
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.4874
                                                {txt}Root MSE          =    {res} 3.7738

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-17.91651{col 36}{space 2} 6.595623{col 47}{space 1}   -2.72{col 56}{space 3}0.009{col 64}{space 4}-31.21785{col 77}{space 3}-4.615165
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2}-13.32851{col 36}{space 2} 9.921227{col 47}{space 1}   -1.34{col 56}{space 3}0.186{col 64}{space 4}-33.33658{col 77}{space 3} 6.679547
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} 1.233857{col 36}{space 2} .2965338{col 47}{space 1}    4.16{col 56}{space 3}0.000{col 64}{space 4}   .63584{col 77}{space 3} 1.831875
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.0043179{col 36}{space 2} .2474276{col 47}{space 1}   -0.02{col 56}{space 3}0.986{col 64}{space 4}-.5033031{col 77}{space 3} .4946673
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} 2.488614{col 36}{space 2}  .664205{col 47}{space 1}    3.75{col 56}{space 3}0.001{col 64}{space 4} 1.149117{col 77}{space 3} 3.828111
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .1432025{col 36}{space 2} .1515281{col 47}{space 1}    0.95{col 56}{space 3}0.350{col 64}{space 4}-.1623831{col 77}{space 3} .4487882
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} -12.5797{col 36}{space 2} 3.441715{col 47}{space 1}   -3.66{col 56}{space 3}0.001{col 64}{space 4}-19.52058{col 77}{space 3}-5.638825
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-15.434881
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2015"

{txt}added macro:
           e(Election) : "{res:2015}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_16: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==2016
{txt}(sum of wgt is 46,454,535)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.44
                                                {txt}Prob > F          = {res}    0.0402
                                                {txt}R-squared         = {res}    0.3128
                                                {txt}Root MSE          =    {res} 1.1388

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} .3929964{col 36}{space 2} .1935078{col 47}{space 1}    2.03{col 56}{space 3}0.048{col 64}{space 4} .0027507{col 77}{space 3} .7832421
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} 2.644198{col 36}{space 2} 1.836454{col 47}{space 1}    1.44{col 56}{space 3}0.157{col 64}{space 4}-1.059363{col 77}{space 3}  6.34776
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.1840015{col 36}{space 2} .1305776{col 47}{space 1}   -1.41{col 56}{space 3}0.166{col 64}{space 4}-.4473364{col 77}{space 3} .0793335
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2} .0133318{col 36}{space 2} .0995174{col 47}{space 1}    0.13{col 56}{space 3}0.894{col 64}{space 4}-.1873641{col 77}{space 3} .2140277
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-2.791874{col 36}{space 2}  .999307{col 47}{space 1}   -2.79{col 56}{space 3}0.008{col 64}{space 4}-4.807169{col 77}{space 3}-.7765795
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0116841{col 36}{space 2} .0566142{col 47}{space 1}    0.21{col 56}{space 3}0.837{col 64}{space 4}-.1024895{col 77}{space 3} .1258576
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 7.326666{col 36}{space 2} 1.670614{col 47}{space 1}    4.39{col 56}{space 3}0.000{col 64}{space 4} 3.957551{col 77}{space 3} 10.69578
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}4.1184794
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2016"

{txt}added macro:
           e(Election) : "{res:2016}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_19_4: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==2019 & month==4
{txt}(sum of wgt is 46,551,452)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     7.81
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.3461
                                                {txt}Root MSE          =    {res}  1.821

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-.4037686{col 36}{space 2} .3515202{col 47}{space 1}   -1.15{col 56}{space 3}0.257{col 64}{space 4}-1.112677{col 77}{space 3} .3051395
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} .3007007{col 36}{space 2} 3.245449{col 47}{space 1}    0.09{col 56}{space 3}0.927{col 64}{space 4}-6.244371{col 77}{space 3} 6.845772
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .4074733{col 36}{space 2} .1146545{col 47}{space 1}    3.55{col 56}{space 3}0.001{col 64}{space 4} .1762504{col 77}{space 3} .6386961
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}  .072701{col 36}{space 2} .1177174{col 47}{space 1}    0.62{col 56}{space 3}0.540{col 64}{space 4}-.1646988{col 77}{space 3} .3101007
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2} 1.432865{col 36}{space 2}   .58585{col 47}{space 1}    2.45{col 56}{space 3}0.019{col 64}{space 4} .2513862{col 77}{space 3} 2.614344
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2} .0518741{col 36}{space 2} .0561542{col 47}{space 1}    0.92{col 56}{space 3}0.361{col 64}{space 4}-.0613717{col 77}{space 3} .1651198
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 2.454487{col 36}{space 2} 2.410327{col 47}{space 1}    1.02{col 56}{space 3}0.314{col 64}{space 4}-2.406402{col 77}{space 3} 7.315375
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}6.0366904
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2019 (4)"

{txt}added macro:
           e(Election) : "{res:2019 (4)}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_19_11: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==2019 & month==11
{txt}(sum of wgt is 46,551,452)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     3.90
                                                {txt}Prob > F          = {res}    0.0034
                                                {txt}R-squared         = {res}    0.3427
                                                {txt}Root MSE          =    {res} 1.0977

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2}-.0419725{col 36}{space 2} .4469507{col 47}{space 1}   -0.09{col 56}{space 3}0.926{col 64}{space 4}-.9433345{col 77}{space 3} .8593896
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} 7.126828{col 36}{space 2} 2.333507{col 47}{space 1}    3.05{col 56}{space 3}0.004{col 64}{space 4} 2.420863{col 77}{space 3} 11.83279
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2} .0036182{col 36}{space 2} .0678088{col 47}{space 1}    0.05{col 56}{space 3}0.958{col 64}{space 4}-.1331313{col 77}{space 3} .1403677
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}  .079579{col 36}{space 2}  .056691{col 47}{space 1}    1.40{col 56}{space 3}0.168{col 64}{space 4}-.0347493{col 77}{space 3} .1939073
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-.4348949{col 36}{space 2} .3969542{col 47}{space 1}   -1.10{col 56}{space 3}0.279{col 64}{space 4}-1.235429{col 77}{space 3} .3656396
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.0183566{col 36}{space 2} .0377516{col 47}{space 1}   -0.49{col 56}{space 3}0.629{col 64}{space 4}-.0944899{col 77}{space 3} .0577767
{txt}{space 17}_cons {c |}{col 24}{res}{space 2}-1.281297{col 36}{space 2} 1.176429{col 47}{space 1}   -1.09{col 56}{space 3}0.282{col 64}{space 4}-3.653793{col 77}{space 3} 1.091199
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-.6449239
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2019 (4)"

{txt}added macro:
           e(Election) : "{res:2019 (4)}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_23: reg var_votes_inc_ours top_prizes_gdp_ours_c expenditure_gdp_ours_c $controls_ours [pw=population], robust , if year==2023
{txt}(sum of wgt is 47,307,133)

Linear regression                               Number of obs     = {res}        50
                                                {txt}F(6, 43)          =  {res}     2.65
                                                {txt}Prob > F          = {res}    0.0280
                                                {txt}R-squared         = {res}    0.3829
                                                {txt}Root MSE          =    {res} 4.1873

{txt}{hline 23}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 24}{c |}{col 36}    Robust
{col 1}    var_votes_inc_ours{col 24}{c |}      Coef.{col 36}   Std. Err.{col 48}      t{col 56}   P>|t|{col 64}     [95% Con{col 77}f. Interval]
{hline 23}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}top_prizes_gdp_ours_c {c |}{col 24}{res}{space 2} 1.862845{col 36}{space 2} 3.539837{col 47}{space 1}    0.53{col 56}{space 3}0.601{col 64}{space 4}-5.275918{col 77}{space 3} 9.001607
{txt}expenditure_gdp_ours_c {c |}{col 24}{res}{space 2} -20.2069{col 36}{space 2} 11.37305{col 47}{space 1}   -1.78{col 56}{space 3}0.083{col 64}{space 4}-43.14284{col 77}{space 3} 2.729031
{txt}{space 1}D_unemployment_rate_2 {c |}{col 24}{res}{space 2}-.0067424{col 36}{space 2} .3585097{col 47}{space 1}   -0.02{col 56}{space 3}0.985{col 64}{space 4} -.729746{col 77}{space 3} .7162613
{txt}{space 12}D_gdp_pc_2 {c |}{col 24}{res}{space 2}-.4140396{col 36}{space 2} .3211754{col 47}{space 1}   -1.29{col 56}{space 3}0.204{col 64}{space 4}-1.061751{col 77}{space 3} .2336723
{txt}{space 15}D_cpi_2 {c |}{col 24}{res}{space 2}-1.031245{col 36}{space 2} 1.192133{col 47}{space 1}   -0.87{col 56}{space 3}0.392{col 64}{space 4}-3.435411{col 77}{space 3} 1.372921
{txt}{space 5}D_housing_price_2 {c |}{col 24}{res}{space 2}-.2149376{col 36}{space 2} .1829405{col 47}{space 1}   -1.17{col 56}{space 3}0.246{col 64}{space 4}-.5838723{col 77}{space 3} .1539971
{txt}{space 17}_cons {c |}{col 24}{res}{space 2} 22.12666{col 36}{space 2} 15.41621{col 47}{space 1}    1.44{col 56}{space 3}0.158{col 64}{space 4}-8.963094{col 77}{space 3} 53.21641
{txt}{hline 23}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}3.7700635
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "2023"

{txt}added macro:
           e(Election) : "{res:2023}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_all: reg var_votes_inc_ours top_prizes_gdp_ours_c c.expenditure_gdp_ours_c##i.year $controls_ours i.province_num [pw=population], robust
{txt}(sum of wgt is 524,884,902)

Linear regression                               Number of obs     = {res}       600
                                                {txt}F(75, 524)        =  {res}    27.39
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8410
                                                {txt}Root MSE          =    {res} 3.3346

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}           var_votes_inc_ours{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}top_prizes_gdp_ours_c {c |}{col 31}{res}{space 2} .0406143{col 43}{space 2} .5318407{col 54}{space 1}    0.08{col 63}{space 3}0.939{col 71}{space 4}-1.004188{col 84}{space 3} 1.085416
{txt}{space 7}expenditure_gdp_ours_c {c |}{col 31}{res}{space 2}-15.84526{col 43}{space 2} 7.587582{col 54}{space 1}   -2.09{col 63}{space 3}0.037{col 71}{space 4}-30.75108{col 84}{space 3}-.9394433
{txt}{space 29} {c |}
{space 25}year {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} .5098109{col 43}{space 2} 3.020038{col 54}{space 1}    0.17{col 63}{space 3}0.866{col 71}{space 4}-5.423059{col 84}{space 3} 6.442681
{txt}{space 24}1996  {c |}{col 31}{res}{space 2}-1.352109{col 43}{space 2} 2.306986{col 54}{space 1}   -0.59{col 63}{space 3}0.558{col 71}{space 4}-5.884186{col 84}{space 3} 3.179968
{txt}{space 24}2000  {c |}{col 31}{res}{space 2} 5.595195{col 43}{space 2} 2.781276{col 54}{space 1}    2.01{col 63}{space 3}0.045{col 71}{space 4} .1313729{col 84}{space 3} 11.05902
{txt}{space 24}2004  {c |}{col 31}{res}{space 2}-10.11083{col 43}{space 2}  2.51934{col 54}{space 1}   -4.01{col 63}{space 3}0.000{col 71}{space 4}-15.06008{col 84}{space 3}-5.161584
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} 3.797945{col 43}{space 2} 3.126197{col 54}{space 1}    1.21{col 63}{space 3}0.225{col 71}{space 4}-2.343474{col 84}{space 3} 9.939364
{txt}{space 24}2011  {c |}{col 31}{res}{space 2}-17.56381{col 43}{space 2} 3.329573{col 54}{space 1}   -5.28{col 63}{space 3}0.000{col 71}{space 4}-24.10476{col 84}{space 3}-11.02285
{txt}{space 24}2015  {c |}{col 31}{res}{space 2}-15.17757{col 43}{space 2}  4.39363{col 54}{space 1}   -3.45{col 63}{space 3}0.001{col 71}{space 4}-23.80886{col 84}{space 3}-6.546273
{txt}{space 24}2016  {c |}{col 31}{res}{space 2}   1.1145{col 43}{space 2} 3.571004{col 54}{space 1}    0.31{col 63}{space 3}0.755{col 71}{space 4}-5.900743{col 84}{space 3} 8.129744
{txt}{space 24}2019  {c |}{col 31}{res}{space 2}-.5309899{col 43}{space 2} 3.943523{col 54}{space 1}   -0.13{col 63}{space 3}0.893{col 71}{space 4}-8.278047{col 84}{space 3} 7.216067
{txt}{space 24}2023  {c |}{col 31}{res}{space 2} 10.20234{col 43}{space 2} 3.832868{col 54}{space 1}    2.66{col 63}{space 3}0.008{col 71}{space 4} 2.672664{col 84}{space 3} 17.73201
{txt}{space 29} {c |}
year#c.expenditure_gdp_ours_c {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} 19.96848{col 43}{space 2} 10.33766{col 54}{space 1}    1.93{col 63}{space 3}0.054{col 71}{space 4}-.3398635{col 84}{space 3} 40.27683
{txt}{space 24}1996  {c |}{col 31}{res}{space 2} 15.88501{col 43}{space 2} 8.138493{col 54}{space 1}    1.95{col 63}{space 3}0.051{col 71}{space 4}-.1030684{col 84}{space 3}  31.8731
{txt}{space 24}2000  {c |}{col 31}{res}{space 2} 9.536037{col 43}{space 2} 8.548183{col 54}{space 1}    1.12{col 63}{space 3}0.265{col 71}{space 4}-7.256881{col 84}{space 3} 26.32896
{txt}{space 24}2004  {c |}{col 31}{res}{space 2} 23.47891{col 43}{space 2} 7.492802{col 54}{space 1}    3.13{col 63}{space 3}0.002{col 71}{space 4} 8.759291{col 84}{space 3} 38.19853
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} 4.188783{col 43}{space 2} 9.720402{col 54}{space 1}    0.43{col 63}{space 3}0.667{col 71}{space 4}-14.90696{col 84}{space 3} 23.28453
{txt}{space 24}2011  {c |}{col 31}{res}{space 2} 21.66113{col 43}{space 2} 8.595022{col 54}{space 1}    2.52{col 63}{space 3}0.012{col 71}{space 4} 4.776196{col 84}{space 3} 38.54606
{txt}{space 24}2015  {c |}{col 31}{res}{space 2} 5.871679{col 43}{space 2} 12.21221{col 54}{space 1}    0.48{col 63}{space 3}0.631{col 71}{space 4}-18.11922{col 84}{space 3} 29.86258
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} 17.80736{col 43}{space 2} 8.192347{col 54}{space 1}    2.17{col 63}{space 3}0.030{col 71}{space 4} 1.713479{col 84}{space 3} 33.90123
{txt}{space 24}2019  {c |}{col 31}{res}{space 2} 18.82174{col 43}{space 2} 10.03439{col 54}{space 1}    1.88{col 63}{space 3}0.061{col 71}{space 4}-.8908415{col 84}{space 3} 38.53432
{txt}{space 24}2023  {c |}{col 31}{res}{space 2}-12.79305{col 43}{space 2} 13.42479{col 54}{space 1}   -0.95{col 63}{space 3}0.341{col 71}{space 4}-39.16608{col 84}{space 3} 13.57998
{txt}{space 29} {c |}
{space 8}D_unemployment_rate_2 {c |}{col 31}{res}{space 2}-.0224749{col 43}{space 2} .0616295{col 54}{space 1}   -0.36{col 63}{space 3}0.715{col 71}{space 4}-.1435461{col 84}{space 3} .0985964
{txt}{space 19}D_gdp_pc_2 {c |}{col 31}{res}{space 2} .0111502{col 43}{space 2} .0246573{col 54}{space 1}    0.45{col 63}{space 3}0.651{col 71}{space 4} -.037289{col 84}{space 3} .0595894
{txt}{space 22}D_cpi_2 {c |}{col 31}{res}{space 2}-.1956273{col 43}{space 2} .1761002{col 54}{space 1}   -1.11{col 63}{space 3}0.267{col 71}{space 4}-.5415764{col 84}{space 3} .1503218
{txt}{space 12}D_housing_price_2 {c |}{col 31}{res}{space 2} .0194601{col 43}{space 2}  .021215{col 54}{space 1}    0.92{col 63}{space 3}0.359{col 71}{space 4}-.0222167{col 84}{space 3}  .061137
{txt}{space 29} {c |}
{space 17}province_num {c |}
{space 23}alava  {c |}{col 31}{res}{space 2} .5269938{col 43}{space 2} 1.762925{col 54}{space 1}    0.30{col 63}{space 3}0.765{col 71}{space 4}-2.936276{col 84}{space 3} 3.990263
{txt}{space 20}albacete  {c |}{col 31}{res}{space 2}-.4165074{col 43}{space 2} 1.011393{col 54}{space 1}   -0.41{col 63}{space 3}0.681{col 71}{space 4} -2.40339{col 84}{space 3} 1.570375
{txt}{space 20}alicante  {c |}{col 31}{res}{space 2} -.260766{col 43}{space 2} 1.297715{col 54}{space 1}   -0.20{col 63}{space 3}0.841{col 71}{space 4} -2.81013{col 84}{space 3} 2.288598
{txt}{space 21}almeria  {c |}{col 31}{res}{space 2}-1.326506{col 43}{space 2} 1.362832{col 54}{space 1}   -0.97{col 63}{space 3}0.331{col 71}{space 4}-4.003792{col 84}{space 3}  1.35078
{txt}{space 20}asturias  {c |}{col 31}{res}{space 2} 1.413404{col 43}{space 2} 1.466605{col 54}{space 1}    0.96{col 63}{space 3}0.336{col 71}{space 4}-1.467743{col 84}{space 3} 4.294551
{txt}{space 23}avila  {c |}{col 31}{res}{space 2} 1.762414{col 43}{space 2}  1.28822{col 54}{space 1}    1.37{col 63}{space 3}0.172{col 71}{space 4}-.7682961{col 84}{space 3} 4.293125
{txt}{space 21}badajoz  {c |}{col 31}{res}{space 2}-.7567938{col 43}{space 2} 1.069811{col 54}{space 1}   -0.71{col 63}{space 3}0.480{col 71}{space 4}-2.858439{col 84}{space 3} 1.344851
{txt}{space 19}barcelona  {c |}{col 31}{res}{space 2} 1.081512{col 43}{space 2} 1.503949{col 54}{space 1}    0.72{col 63}{space 3}0.472{col 71}{space 4}-1.872999{col 84}{space 3} 4.036023
{txt}{space 22}burgos  {c |}{col 31}{res}{space 2} .7563718{col 43}{space 2}  1.20401{col 54}{space 1}    0.63{col 63}{space 3}0.530{col 71}{space 4}-1.608908{col 84}{space 3} 3.121652
{txt}{space 21}caceres  {c |}{col 31}{res}{space 2}-.0683396{col 43}{space 2} 1.007598{col 54}{space 1}   -0.07{col 63}{space 3}0.946{col 71}{space 4}-2.047767{col 84}{space 3} 1.911088
{txt}{space 23}cadiz  {c |}{col 31}{res}{space 2}-2.447881{col 43}{space 2} 1.296629{col 54}{space 1}   -1.89{col 63}{space 3}0.060{col 71}{space 4}-4.995111{col 84}{space 3} .0993488
{txt}{space 19}cantabria  {c |}{col 31}{res}{space 2}-.0641992{col 43}{space 2} 1.310995{col 54}{space 1}   -0.05{col 63}{space 3}0.961{col 71}{space 4} -2.63965{col 84}{space 3} 2.511252
{txt}{space 19}castellon  {c |}{col 31}{res}{space 2}-.5226932{col 43}{space 2} 1.194166{col 54}{space 1}   -0.44{col 63}{space 3}0.662{col 71}{space 4}-2.868635{col 84}{space 3} 1.823248
{txt}{space 17}ciudad real  {c |}{col 31}{res}{space 2}-.0625598{col 43}{space 2} 1.227223{col 54}{space 1}   -0.05{col 63}{space 3}0.959{col 71}{space 4}-2.473441{col 84}{space 3} 2.348321
{txt}{space 21}cordoba  {c |}{col 31}{res}{space 2}-.7769307{col 43}{space 2} 1.060594{col 54}{space 1}   -0.73{col 63}{space 3}0.464{col 71}{space 4} -2.86047{col 84}{space 3} 1.306609
{txt}{space 22}cuenca  {c |}{col 31}{res}{space 2} .7868171{col 43}{space 2} 1.377397{col 54}{space 1}    0.57{col 63}{space 3}0.568{col 71}{space 4} -1.91908{col 84}{space 3} 3.492715
{txt}{space 20}gipuzkoa  {c |}{col 31}{res}{space 2} 1.611465{col 43}{space 2} 1.891598{col 54}{space 1}    0.85{col 63}{space 3}0.395{col 71}{space 4}-2.104582{col 84}{space 3} 5.327512
{txt}{space 22}girona  {c |}{col 31}{res}{space 2} 1.847324{col 43}{space 2} 1.790195{col 54}{space 1}    1.03{col 63}{space 3}0.303{col 71}{space 4}-1.669517{col 84}{space 3} 5.364164
{txt}{space 21}granada  {c |}{col 31}{res}{space 2}-.6970102{col 43}{space 2}  .993209{col 54}{space 1}   -0.70{col 63}{space 3}0.483{col 71}{space 4}-2.648171{col 84}{space 3} 1.254151
{txt}{space 17}guadalajara  {c |}{col 31}{res}{space 2}-.6874728{col 43}{space 2} 1.148558{col 54}{space 1}   -0.60{col 63}{space 3}0.550{col 71}{space 4}-2.943816{col 84}{space 3}  1.56887
{txt}{space 22}huelva  {c |}{col 31}{res}{space 2}-1.989172{col 43}{space 2} 1.427575{col 54}{space 1}   -1.39{col 63}{space 3}0.164{col 71}{space 4}-4.793645{col 84}{space 3} .8153013
{txt}{space 22}huesca  {c |}{col 31}{res}{space 2}-.1363979{col 43}{space 2}   1.2618{col 54}{space 1}   -0.11{col 63}{space 3}0.914{col 71}{space 4}-2.615206{col 84}{space 3}  2.34241
{txt}{space 14}islas baleares  {c |}{col 31}{res}{space 2}-.4080727{col 43}{space 2} 1.552297{col 54}{space 1}   -0.26{col 63}{space 3}0.793{col 71}{space 4}-3.457562{col 84}{space 3} 2.641417
{txt}{space 24}jaen  {c |}{col 31}{res}{space 2}-.9126838{col 43}{space 2}  1.06722{col 54}{space 1}   -0.86{col 63}{space 3}0.393{col 71}{space 4} -3.00924{col 84}{space 3} 1.183872
{txt}{space 20}la rioja  {c |}{col 31}{res}{space 2} .5812575{col 43}{space 2} .9877839{col 54}{space 1}    0.59{col 63}{space 3}0.556{col 71}{space 4}-1.359246{col 84}{space 3} 2.521761
{txt}{space 18}las palmas  {c |}{col 31}{res}{space 2}-.5861888{col 43}{space 2} 1.652519{col 54}{space 1}   -0.35{col 63}{space 3}0.723{col 71}{space 4}-3.832565{col 84}{space 3} 2.660187
{txt}{space 24}leon  {c |}{col 31}{res}{space 2}-.0866053{col 43}{space 2} 1.183984{col 54}{space 1}   -0.07{col 63}{space 3}0.942{col 71}{space 4}-2.412543{col 84}{space 3} 2.239332
{txt}{space 22}lleida  {c |}{col 31}{res}{space 2} 2.728469{col 43}{space 2} 2.214683{col 54}{space 1}    1.23{col 63}{space 3}0.219{col 71}{space 4}-1.622279{col 84}{space 3} 7.079217
{txt}{space 24}lugo  {c |}{col 31}{res}{space 2} .9706371{col 43}{space 2} 1.231928{col 54}{space 1}    0.79{col 63}{space 3}0.431{col 71}{space 4}-1.449488{col 84}{space 3} 3.390762
{txt}{space 22}madrid  {c |}{col 31}{res}{space 2}-1.318075{col 43}{space 2} 1.321372{col 54}{space 1}   -1.00{col 63}{space 3}0.319{col 71}{space 4}-3.913913{col 84}{space 3} 1.277762
{txt}{space 22}malaga  {c |}{col 31}{res}{space 2}-2.245416{col 43}{space 2} 1.156985{col 54}{space 1}   -1.94{col 63}{space 3}0.053{col 71}{space 4}-4.518314{col 84}{space 3} .0274826
{txt}{space 22}murcia  {c |}{col 31}{res}{space 2}-.5980519{col 43}{space 2} 1.527467{col 54}{space 1}   -0.39{col 63}{space 3}0.696{col 71}{space 4}-3.598762{col 84}{space 3} 2.402659
{txt}{space 21}navarra  {c |}{col 31}{res}{space 2} .5163613{col 43}{space 2} 1.687973{col 54}{space 1}    0.31{col 63}{space 3}0.760{col 71}{space 4}-2.799664{col 84}{space 3} 3.832386
{txt}{space 21}ourense  {c |}{col 31}{res}{space 2} 2.223945{col 43}{space 2} 1.513108{col 54}{space 1}    1.47{col 63}{space 3}0.142{col 71}{space 4}-.7485589{col 84}{space 3} 5.196448
{txt}{space 20}palencia  {c |}{col 31}{res}{space 2}  .990265{col 43}{space 2} 1.142815{col 54}{space 1}    0.87{col 63}{space 3}0.387{col 71}{space 4}-1.254797{col 84}{space 3} 3.235327
{txt}{space 18}pontevedra  {c |}{col 31}{res}{space 2} .4707786{col 43}{space 2}  1.24066{col 54}{space 1}    0.38{col 63}{space 3}0.705{col 71}{space 4}  -1.9665{col 84}{space 3} 2.908057
{txt}{space 19}salamanca  {c |}{col 31}{res}{space 2} .2534271{col 43}{space 2} 1.020511{col 54}{space 1}    0.25{col 63}{space 3}0.804{col 71}{space 4}-1.751368{col 84}{space 3} 2.258222
{txt}{space 6}santa cruz de tenerife  {c |}{col 31}{res}{space 2} .1346857{col 43}{space 2} 1.129256{col 54}{space 1}    0.12{col 63}{space 3}0.905{col 71}{space 4} -2.08374{col 84}{space 3} 2.353112
{txt}{space 21}segovia  {c |}{col 31}{res}{space 2} 1.071591{col 43}{space 2} 1.529134{col 54}{space 1}    0.70{col 63}{space 3}0.484{col 71}{space 4}-1.932395{col 84}{space 3} 4.075577
{txt}{space 21}sevilla  {c |}{col 31}{res}{space 2}-1.522955{col 43}{space 2} 1.273533{col 54}{space 1}   -1.20{col 63}{space 3}0.232{col 71}{space 4}-4.024813{col 84}{space 3} .9789035
{txt}{space 23}soria  {c |}{col 31}{res}{space 2} 1.786019{col 43}{space 2} 2.735107{col 54}{space 1}    0.65{col 63}{space 3}0.514{col 71}{space 4}-3.587104{col 84}{space 3} 7.159141
{txt}{space 19}tarragona  {c |}{col 31}{res}{space 2} 1.077009{col 43}{space 2} 1.762837{col 54}{space 1}    0.61{col 63}{space 3}0.541{col 71}{space 4}-2.386088{col 84}{space 3} 4.540106
{txt}{space 22}teruel  {c |}{col 31}{res}{space 2}-.0422458{col 43}{space 2} 1.551628{col 54}{space 1}   -0.03{col 63}{space 3}0.978{col 71}{space 4}-3.090422{col 84}{space 3}  3.00593
{txt}{space 22}toledo  {c |}{col 31}{res}{space 2}-.5899005{col 43}{space 2} 1.090487{col 54}{space 1}   -0.54{col 63}{space 3}0.589{col 71}{space 4}-2.732164{col 84}{space 3} 1.552363
{txt}{space 20}valencia  {c |}{col 31}{res}{space 2} -.332406{col 43}{space 2} 1.270676{col 54}{space 1}   -0.26{col 63}{space 3}0.794{col 71}{space 4} -2.82865{col 84}{space 3} 2.163839
{txt}{space 18}valladolid  {c |}{col 31}{res}{space 2}  -.19189{col 43}{space 2} 1.019132{col 54}{space 1}   -0.19{col 63}{space 3}0.851{col 71}{space 4}-2.193976{col 84}{space 3} 1.810196
{txt}{space 21}vizcaya  {c |}{col 31}{res}{space 2} 1.897693{col 43}{space 2} 1.621347{col 54}{space 1}    1.17{col 63}{space 3}0.242{col 71}{space 4}-1.287446{col 84}{space 3} 5.082831
{txt}{space 22}zamora  {c |}{col 31}{res}{space 2} 1.193336{col 43}{space 2}  1.16316{col 54}{space 1}    1.03{col 63}{space 3}0.305{col 71}{space 4}-1.091692{col 84}{space 3} 3.478365
{txt}{space 20}zaragoza  {c |}{col 31}{res}{space 2}-1.348745{col 43}{space 2} 1.389744{col 54}{space 1}   -0.97{col 63}{space 3}0.332{col 71}{space 4}-4.078898{col 84}{space 3} 1.381408
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2}  2.91335{col 43}{space 2} 3.496088{col 54}{space 1}    0.83{col 63}{space 3}0.405{col 71}{space 4}-3.954721{col 84}{space 3} 9.781421
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-2.0073051
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "All"

{txt}added macro:
           e(Election) : "{res:All}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_all_ex15: reg var_votes_inc_ours top_prizes_gdp_ours_c c.expenditure_gdp_ours_c##i.year $controls_ours i.province_num [pw=population], robust, if year!=2015
{txt}(sum of wgt is 478,277,577)

Linear regression                               Number of obs     = {res}       550
                                                {txt}F(73, 476)        =  {res}    27.33
                                                {txt}Prob > F          = {res}    0.0000
                                                {txt}R-squared         = {res}    0.8080
                                                {txt}Root MSE          =    {res}  3.175

{txt}{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}           var_votes_inc_ours{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}top_prizes_gdp_ours_c {c |}{col 31}{res}{space 2} .1519773{col 43}{space 2}  .466978{col 54}{space 1}    0.33{col 63}{space 3}0.745{col 71}{space 4}-.7656159{col 84}{space 3}  1.06957
{txt}{space 7}expenditure_gdp_ours_c {c |}{col 31}{res}{space 2} -17.7821{col 43}{space 2} 7.653221{col 54}{space 1}   -2.32{col 63}{space 3}0.021{col 71}{space 4}-32.82037{col 84}{space 3}-2.743823
{txt}{space 29} {c |}
{space 25}year {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} 1.440988{col 43}{space 2} 3.120713{col 54}{space 1}    0.46{col 63}{space 3}0.644{col 71}{space 4}-4.691088{col 84}{space 3} 7.573064
{txt}{space 24}1996  {c |}{col 31}{res}{space 2}-1.616757{col 43}{space 2} 2.205388{col 54}{space 1}   -0.73{col 63}{space 3}0.464{col 71}{space 4}-5.950256{col 84}{space 3} 2.716743
{txt}{space 24}2000  {c |}{col 31}{res}{space 2} 4.867609{col 43}{space 2} 2.704489{col 54}{space 1}    1.80{col 63}{space 3}0.073{col 71}{space 4}-.4466043{col 84}{space 3} 10.18182
{txt}{space 24}2004  {c |}{col 31}{res}{space 2}-9.743528{col 43}{space 2} 2.388604{col 54}{space 1}   -4.08{col 63}{space 3}0.000{col 71}{space 4}-14.43704{col 84}{space 3}-5.050016
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} 4.256594{col 43}{space 2} 3.307815{col 54}{space 1}    1.29{col 63}{space 3}0.199{col 71}{space 4} -2.24313{col 84}{space 3} 10.75632
{txt}{space 24}2011  {c |}{col 31}{res}{space 2}-16.84812{col 43}{space 2}  3.29685{col 54}{space 1}   -5.11{col 63}{space 3}0.000{col 71}{space 4} -23.3263{col 84}{space 3}-10.36994
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} .8240453{col 43}{space 2} 3.631992{col 54}{space 1}    0.23{col 63}{space 3}0.821{col 71}{space 4}-6.312674{col 84}{space 3} 7.960764
{txt}{space 24}2019  {c |}{col 31}{res}{space 2}-.9675911{col 43}{space 2} 4.015541{col 54}{space 1}   -0.24{col 63}{space 3}0.810{col 71}{space 4} -8.85797{col 84}{space 3} 6.922787
{txt}{space 24}2023  {c |}{col 31}{res}{space 2} 10.50135{col 43}{space 2} 3.951263{col 54}{space 1}    2.66{col 63}{space 3}0.008{col 71}{space 4} 2.737271{col 84}{space 3} 18.26542
{txt}{space 29} {c |}
year#c.expenditure_gdp_ours_c {c |}
{space 24}1993  {c |}{col 31}{res}{space 2} 20.31299{col 43}{space 2} 10.55028{col 54}{space 1}    1.93{col 63}{space 3}0.055{col 71}{space 4}-.4179016{col 84}{space 3} 41.04388
{txt}{space 24}1996  {c |}{col 31}{res}{space 2} 16.73949{col 43}{space 2} 7.702177{col 54}{space 1}    2.17{col 63}{space 3}0.030{col 71}{space 4} 1.605022{col 84}{space 3} 31.87396
{txt}{space 24}2000  {c |}{col 31}{res}{space 2} 9.610459{col 43}{space 2} 7.956082{col 54}{space 1}    1.21{col 63}{space 3}0.228{col 71}{space 4}-6.022926{col 84}{space 3} 25.24384
{txt}{space 24}2004  {c |}{col 31}{res}{space 2} 23.06836{col 43}{space 2} 7.034038{col 54}{space 1}    3.28{col 63}{space 3}0.001{col 71}{space 4} 9.246753{col 84}{space 3} 36.88996
{txt}{space 24}2008  {c |}{col 31}{res}{space 2} 4.685034{col 43}{space 2}  10.2449{col 54}{space 1}    0.46{col 63}{space 3}0.648{col 71}{space 4}-15.44579{col 84}{space 3} 24.81586
{txt}{space 24}2011  {c |}{col 31}{res}{space 2} 21.86694{col 43}{space 2} 8.184134{col 54}{space 1}    2.67{col 63}{space 3}0.008{col 71}{space 4} 5.785446{col 84}{space 3} 37.94844
{txt}{space 24}2016  {c |}{col 31}{res}{space 2} 17.99823{col 43}{space 2} 7.816864{col 54}{space 1}    2.30{col 63}{space 3}0.022{col 71}{space 4} 2.638404{col 84}{space 3} 33.35806
{txt}{space 24}2019  {c |}{col 31}{res}{space 2} 18.89803{col 43}{space 2} 9.792136{col 54}{space 1}    1.93{col 63}{space 3}0.054{col 71}{space 4}-.3431292{col 84}{space 3} 38.13919
{txt}{space 24}2023  {c |}{col 31}{res}{space 2}-13.45849{col 43}{space 2} 13.80548{col 54}{space 1}   -0.97{col 63}{space 3}0.330{col 71}{space 4}-40.58571{col 84}{space 3} 13.66873
{txt}{space 29} {c |}
{space 8}D_unemployment_rate_2 {c |}{col 31}{res}{space 2}-.1053286{col 43}{space 2} .0605575{col 54}{space 1}   -1.74{col 63}{space 3}0.083{col 71}{space 4}-.2243217{col 84}{space 3} .0136644
{txt}{space 19}D_gdp_pc_2 {c |}{col 31}{res}{space 2} .0221991{col 43}{space 2} .0239437{col 54}{space 1}    0.93{col 63}{space 3}0.354{col 71}{space 4}-.0248493{col 84}{space 3} .0692475
{txt}{space 22}D_cpi_2 {c |}{col 31}{res}{space 2}-.2146731{col 43}{space 2} .1815436{col 54}{space 1}   -1.18{col 63}{space 3}0.238{col 71}{space 4} -.571399{col 84}{space 3} .1420529
{txt}{space 12}D_housing_price_2 {c |}{col 31}{res}{space 2}  .014571{col 43}{space 2} .0207283{col 54}{space 1}    0.70{col 63}{space 3}0.482{col 71}{space 4}-.0261593{col 84}{space 3} .0553012
{txt}{space 29} {c |}
{space 17}province_num {c |}
{space 23}alava  {c |}{col 31}{res}{space 2}-.3214167{col 43}{space 2} 1.794596{col 54}{space 1}   -0.18{col 63}{space 3}0.858{col 71}{space 4}-3.847726{col 84}{space 3} 3.204893
{txt}{space 20}albacete  {c |}{col 31}{res}{space 2}-.2227442{col 43}{space 2} 1.101833{col 54}{space 1}   -0.20{col 63}{space 3}0.840{col 71}{space 4}-2.387802{col 84}{space 3} 1.942314
{txt}{space 20}alicante  {c |}{col 31}{res}{space 2} .4698413{col 43}{space 2}     1.26{col 54}{space 1}    0.37{col 63}{space 3}0.709{col 71}{space 4}-2.006008{col 84}{space 3} 2.945691
{txt}{space 21}almeria  {c |}{col 31}{res}{space 2}-1.024935{col 43}{space 2} 1.412973{col 54}{space 1}   -0.73{col 63}{space 3}0.469{col 71}{space 4} -3.80137{col 84}{space 3} 1.751501
{txt}{space 20}asturias  {c |}{col 31}{res}{space 2} .5860524{col 43}{space 2} 1.276973{col 54}{space 1}    0.46{col 63}{space 3}0.646{col 71}{space 4}-1.923148{col 84}{space 3} 3.095253
{txt}{space 23}avila  {c |}{col 31}{res}{space 2} 2.013238{col 43}{space 2} 1.373237{col 54}{space 1}    1.47{col 63}{space 3}0.143{col 71}{space 4} -.685117{col 84}{space 3} 4.711594
{txt}{space 21}badajoz  {c |}{col 31}{res}{space 2}-.9544309{col 43}{space 2} 1.195531{col 54}{space 1}   -0.80{col 63}{space 3}0.425{col 71}{space 4}-3.303601{col 84}{space 3}  1.39474
{txt}{space 19}barcelona  {c |}{col 31}{res}{space 2} .5031821{col 43}{space 2}  1.58043{col 54}{space 1}    0.32{col 63}{space 3}0.750{col 71}{space 4}  -2.6023{col 84}{space 3} 3.608665
{txt}{space 22}burgos  {c |}{col 31}{res}{space 2} .8146673{col 43}{space 2} 1.295968{col 54}{space 1}    0.63{col 63}{space 3}0.530{col 71}{space 4}-1.731859{col 84}{space 3} 3.361193
{txt}{space 21}caceres  {c |}{col 31}{res}{space 2}  .021813{col 43}{space 2} 1.094386{col 54}{space 1}    0.02{col 63}{space 3}0.984{col 71}{space 4}-2.128613{col 84}{space 3} 2.172239
{txt}{space 23}cadiz  {c |}{col 31}{res}{space 2} -2.54359{col 43}{space 2}   1.3899{col 54}{space 1}   -1.83{col 63}{space 3}0.068{col 71}{space 4}-5.274688{col 84}{space 3} .1875082
{txt}{space 19}cantabria  {c |}{col 31}{res}{space 2}-.1761643{col 43}{space 2} 1.435187{col 54}{space 1}   -0.12{col 63}{space 3}0.902{col 71}{space 4}-2.996249{col 84}{space 3}  2.64392
{txt}{space 19}castellon  {c |}{col 31}{res}{space 2} .0400577{col 43}{space 2} 1.199548{col 54}{space 1}    0.03{col 63}{space 3}0.973{col 71}{space 4}-2.317006{col 84}{space 3} 2.397121
{txt}{space 17}ciudad real  {c |}{col 31}{res}{space 2} .0818648{col 43}{space 2} 1.336143{col 54}{space 1}    0.06{col 63}{space 3}0.951{col 71}{space 4}-2.543604{col 84}{space 3} 2.707333
{txt}{space 21}cordoba  {c |}{col 31}{res}{space 2}-1.098071{col 43}{space 2} 1.148767{col 54}{space 1}   -0.96{col 63}{space 3}0.340{col 71}{space 4}-3.355353{col 84}{space 3}  1.15921
{txt}{space 22}cuenca  {c |}{col 31}{res}{space 2} .8401595{col 43}{space 2} 1.474053{col 54}{space 1}    0.57{col 63}{space 3}0.569{col 71}{space 4}-2.056295{col 84}{space 3} 3.736614
{txt}{space 20}gipuzkoa  {c |}{col 31}{res}{space 2} .6047007{col 43}{space 2} 1.866714{col 54}{space 1}    0.32{col 63}{space 3}0.746{col 71}{space 4}-3.063318{col 84}{space 3} 4.272719
{txt}{space 22}girona  {c |}{col 31}{res}{space 2} 1.191206{col 43}{space 2} 1.884984{col 54}{space 1}    0.63{col 63}{space 3}0.528{col 71}{space 4}-2.512712{col 84}{space 3} 4.895124
{txt}{space 21}granada  {c |}{col 31}{res}{space 2}-.8152531{col 43}{space 2} 1.077079{col 54}{space 1}   -0.76{col 63}{space 3}0.449{col 71}{space 4}-2.931671{col 84}{space 3} 1.301165
{txt}{space 17}guadalajara  {c |}{col 31}{res}{space 2}-.4340144{col 43}{space 2}  1.22971{col 54}{space 1}   -0.35{col 63}{space 3}0.724{col 71}{space 4}-2.850346{col 84}{space 3} 1.982317
{txt}{space 22}huelva  {c |}{col 31}{res}{space 2}-2.420688{col 43}{space 2} 1.543366{col 54}{space 1}   -1.57{col 63}{space 3}0.117{col 71}{space 4}-5.453341{col 84}{space 3} .6119652
{txt}{space 22}huesca  {c |}{col 31}{res}{space 2}-.1429174{col 43}{space 2} 1.347241{col 54}{space 1}   -0.11{col 63}{space 3}0.916{col 71}{space 4}-2.790193{col 84}{space 3} 2.504358
{txt}{space 14}islas baleares  {c |}{col 31}{res}{space 2} .1080252{col 43}{space 2} 1.554958{col 54}{space 1}    0.07{col 63}{space 3}0.945{col 71}{space 4}-2.947405{col 84}{space 3} 3.163455
{txt}{space 24}jaen  {c |}{col 31}{res}{space 2}-1.267009{col 43}{space 2} 1.150156{col 54}{space 1}   -1.10{col 63}{space 3}0.271{col 71}{space 4}-3.527019{col 84}{space 3} .9930006
{txt}{space 20}la rioja  {c |}{col 31}{res}{space 2} .7818096{col 43}{space 2} 1.100278{col 54}{space 1}    0.71{col 63}{space 3}0.478{col 71}{space 4}-1.380194{col 84}{space 3} 2.943813
{txt}{space 18}las palmas  {c |}{col 31}{res}{space 2}-.0122123{col 43}{space 2} 1.613584{col 54}{space 1}   -0.01{col 63}{space 3}0.994{col 71}{space 4} -3.18284{col 84}{space 3} 3.158415
{txt}{space 24}leon  {c |}{col 31}{res}{space 2}-.0173082{col 43}{space 2} 1.276183{col 54}{space 1}   -0.01{col 63}{space 3}0.989{col 71}{space 4}-2.524957{col 84}{space 3} 2.490341
{txt}{space 22}lleida  {c |}{col 31}{res}{space 2} 2.444364{col 43}{space 2} 2.274266{col 54}{space 1}    1.07{col 63}{space 3}0.283{col 71}{space 4}-2.024479{col 84}{space 3} 6.913207
{txt}{space 24}lugo  {c |}{col 31}{res}{space 2} .8194754{col 43}{space 2} 1.349082{col 54}{space 1}    0.61{col 63}{space 3}0.544{col 71}{space 4}-1.831417{col 84}{space 3} 3.470368
{txt}{space 22}madrid  {c |}{col 31}{res}{space 2}-1.233113{col 43}{space 2} 1.446748{col 54}{space 1}   -0.85{col 63}{space 3}0.394{col 71}{space 4}-4.075915{col 84}{space 3} 1.609689
{txt}{space 22}malaga  {c |}{col 31}{res}{space 2}-1.967305{col 43}{space 2} 1.211103{col 54}{space 1}   -1.62{col 63}{space 3}0.105{col 71}{space 4}-4.347074{col 84}{space 3} .4124648
{txt}{space 22}murcia  {c |}{col 31}{res}{space 2} .2239803{col 43}{space 2} 1.433772{col 54}{space 1}    0.16{col 63}{space 3}0.876{col 71}{space 4}-2.593325{col 84}{space 3} 3.041285
{txt}{space 21}navarra  {c |}{col 31}{res}{space 2} -.129697{col 43}{space 2} 1.760598{col 54}{space 1}   -0.07{col 63}{space 3}0.941{col 71}{space 4}-3.589201{col 84}{space 3} 3.329807
{txt}{space 21}ourense  {c |}{col 31}{res}{space 2} 1.976099{col 43}{space 2} 1.623989{col 54}{space 1}    1.22{col 63}{space 3}0.224{col 71}{space 4}-1.214975{col 84}{space 3} 5.167174
{txt}{space 20}palencia  {c |}{col 31}{res}{space 2} .9380602{col 43}{space 2} 1.224721{col 54}{space 1}    0.77{col 63}{space 3}0.444{col 71}{space 4}-1.468469{col 84}{space 3} 3.344589
{txt}{space 18}pontevedra  {c |}{col 31}{res}{space 2} .5343403{col 43}{space 2} 1.360356{col 54}{space 1}    0.39{col 63}{space 3}0.695{col 71}{space 4}-2.138706{col 84}{space 3} 3.207387
{txt}{space 19}salamanca  {c |}{col 31}{res}{space 2} .3545924{col 43}{space 2} 1.124745{col 54}{space 1}    0.32{col 63}{space 3}0.753{col 71}{space 4}-1.855486{col 84}{space 3} 2.564671
{txt}{space 6}santa cruz de tenerife  {c |}{col 31}{res}{space 2} .1784457{col 43}{space 2} 1.225743{col 54}{space 1}    0.15{col 63}{space 3}0.884{col 71}{space 4}-2.230091{col 84}{space 3} 2.586982
{txt}{space 21}segovia  {c |}{col 31}{res}{space 2}  1.36524{col 43}{space 2} 1.612431{col 54}{space 1}    0.85{col 63}{space 3}0.398{col 71}{space 4}-1.803122{col 84}{space 3} 4.533603
{txt}{space 21}sevilla  {c |}{col 31}{res}{space 2}-2.082917{col 43}{space 2}  1.34626{col 54}{space 1}   -1.55{col 63}{space 3}0.122{col 71}{space 4}-4.728263{col 84}{space 3} .5624301
{txt}{space 23}soria  {c |}{col 31}{res}{space 2}  2.06696{col 43}{space 2} 2.755452{col 54}{space 1}    0.75{col 63}{space 3}0.454{col 71}{space 4}-3.347394{col 84}{space 3} 7.481314
{txt}{space 19}tarragona  {c |}{col 31}{res}{space 2} .6828473{col 43}{space 2} 1.958976{col 54}{space 1}    0.35{col 63}{space 3}0.728{col 71}{space 4}-3.166462{col 84}{space 3} 4.532156
{txt}{space 22}teruel  {c |}{col 31}{res}{space 2} -.050692{col 43}{space 2} 1.695869{col 54}{space 1}   -0.03{col 63}{space 3}0.976{col 71}{space 4}-3.383007{col 84}{space 3} 3.281623
{txt}{space 22}toledo  {c |}{col 31}{res}{space 2}-.3818303{col 43}{space 2} 1.176918{col 54}{space 1}   -0.32{col 63}{space 3}0.746{col 71}{space 4}-2.694428{col 84}{space 3} 1.930767
{txt}{space 20}valencia  {c |}{col 31}{res}{space 2} .2795885{col 43}{space 2} 1.242524{col 54}{space 1}    0.23{col 63}{space 3}0.822{col 71}{space 4}-2.161923{col 84}{space 3} 2.721099
{txt}{space 18}valladolid  {c |}{col 31}{res}{space 2}-.3079895{col 43}{space 2}   1.1431{col 54}{space 1}   -0.27{col 63}{space 3}0.788{col 71}{space 4}-2.554136{col 84}{space 3} 1.938158
{txt}{space 21}vizcaya  {c |}{col 31}{res}{space 2} 1.174181{col 43}{space 2}   1.5577{col 54}{space 1}    0.75{col 63}{space 3}0.451{col 71}{space 4}-1.886637{col 84}{space 3} 4.234999
{txt}{space 22}zamora  {c |}{col 31}{res}{space 2} 1.253434{col 43}{space 2} 1.261704{col 54}{space 1}    0.99{col 63}{space 3}0.321{col 71}{space 4}-1.225765{col 84}{space 3} 3.732632
{txt}{space 20}zaragoza  {c |}{col 31}{res}{space 2}-1.413929{col 43}{space 2} 1.535119{col 54}{space 1}   -0.92{col 63}{space 3}0.357{col 71}{space 4}-4.430377{col 84}{space 3} 1.602519
{txt}{space 29} {c |}
{space 24}_cons {c |}{col 31}{res}{space 2} 3.489376{col 43}{space 2} 3.660569{col 54}{space 1}    0.95{col 63}{space 3}0.341{col 71}{space 4}-3.703496{col 84}{space 3} 10.68225
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-.69881098
{txt}
{com}. estadd local Estimation "OLS"

{txt}added macro:
         e(Estimation) : "{res:OLS}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year "$\checkmark$"

{txt}added macro:
               e(Year) : "{res:$\checkmark$}"

{com}. estadd local Province "$\checkmark$"

{txt}added macro:
           e(Province) : "{res:$\checkmark$}"

{com}. estadd local Cluster "$\times$"

{txt}added macro:
            e(Cluster) : "{res:$\times$}"

{com}. estadd local Controls "$\checkmark$"

{txt}added macro:
           e(Controls) : "{res:$\checkmark$}"

{com}. estadd local Election "All"

{txt}added macro:
           e(Election) : "{res:All}"

{com}. estadd local Pop_weights "$\checkmark$"

{txt}added macro:
        e(Pop_weights) : "{res:$\checkmark$}"

{com}. 
. eststo col_4_meta: reg var_votes_inc_ours var_votes_inc_ours

{txt}      Source {c |}       SS           df       MS      Number of obs   ={res}       600
{txt}{hline 13}{c +}{hline 34}   F(1, 598)       = {res}        .
{txt}       Model {c |} {res} 32423.3892         1  32423.3892   {txt}Prob > F        ={res}         .
{txt}    Residual {c |} {res}          0       598           0   {txt}R-squared       ={res}    1.0000
{txt}{hline 13}{c +}{hline 34}   Adj R-squared   ={res}    1.0000
{txt}       Total {c |} {res} 32423.3892       599  54.1291974   {txt}Root MSE        =   {res}      0

{txt}{hline 19}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}var_votes_inc_ours{col 20}{c |}      Coef.{col 32}   Std. Err.{col 44}      t{col 52}   P>|t|{col 60}     [95% Con{col 73}f. Interval]
{hline 19}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
var_votes_inc_ours {c |}{col 20}{res}{space 2}        1{col 32}{space 2}        .{col 43}{space 1}       .{col 52}{space 3}    .{col 60}{space 4}        .{col 73}{space 3}        .
{txt}{space 13}_cons {c |}{col 20}{res}{space 2} 4.44e-16{col 32}{space 2}        .{col 43}{space 1}       .{col 52}{space 3}    .{col 60}{space 4}        .{col 73}{space 3}        .
{txt}{hline 19}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. summarize var_votes_inc_ours [aweight=population] if e(sample), meanonly
{txt}
{com}. estadd scalar MeanDV = r(mean)

{txt}added scalar:
             e(MeanDV) =  {res}-2.0073051
{txt}
{com}. estadd local Estimation "Meta"

{txt}added macro:
         e(Estimation) : "{res:Meta}"

{com}. estadd local Data "Ours"

{txt}added macro:
               e(Data) : "{res:Ours}"

{com}. estadd local Year ""

{txt}added macro:
               e(Year) : "{res:}"

{com}. estadd local Province ""

{txt}added macro:
           e(Province) : "{res:}"

{com}. estadd local Cluster ""

{txt}added macro:
            e(Cluster) : "{res:}"

{com}. estadd local Controls ""

{txt}added macro:
           e(Controls) : "{res:}"

{com}. estadd local Election "All"

{txt}added macro:
           e(Election) : "{res:All}"

{com}. estadd local Pop_weights ""

{txt}added macro:
        e(Pop_weights) : "{res:}"

{com}. 
. * Table A11: Electoral Results (Using Only the Latest Lottery) with Population Weights, by Election, Using Our Data
. esttab col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 col_4_all col_4_meta using ${c -(}tables{c )-}electoral_results_our_data_by_election_pw_inter_y.tex, ///
>                 keep(top_prizes_gdp_ours_c)  ///
>                 nocon r2 ///
>                 mtitles se mtitles("Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." ///
>                                                         "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." "Vote Incumb." ///
>                                                         "Vote Incumb.")  ///
>                 coeflabels(top_prizes_gdp_ours_c "Prev. Year Top Prizes")  ///
>                                         scalars("MeanDV Outcome Mean" "Estimation Estimation" "Data Data" "Year Year FEs" "Province Province FEs" "Controls Controls" "Cluster Cluster Province" "Election Election" "Pop_weights Pop. Weights")  ///
>         star(* 0.05 ** 0.01) b(%9.3f) replace
{res}{txt}(note: file Results/Tables_Electoral/electoral_results_our_data_by_election_pw_inter_y.tex not found)
(output written to {browse  `"Results/Tables_Electoral/electoral_results_our_data_by_election_pw_inter_y.tex"'})

{com}.                 
. 
. 
. **----------------------------------------------------------------------------**
. *** META ANALYSIS (WITH POPULATION WEIGHTS)
. **----------------------------------------------------------------------------**
.  
. * Pooled
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_ours_c]
{txt}  4{com}.     local se = _se[top_prizes_gdp_ours_c]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_89:col_4_89} are active now)
(results {stata estimates replay col_4_93:col_4_93} are active now)
(results {stata estimates replay col_4_96:col_4_96} are active now)
(results {stata estimates replay col_4_00:col_4_00} are active now)
(results {stata estimates replay col_4_04:col_4_04} are active now)
(results {stata estimates replay col_4_08:col_4_08} are active now)
(results {stata estimates replay col_4_11:col_4_11} are active now)
(results {stata estimates replay col_4_15:col_4_15} are active now)
(results {stata estimates replay col_4_16:col_4_16} are active now)
(results {stata estimates replay col_4_19_4:col_4_19_4} are active now)
(results {stata estimates replay col_4_19_11:col_4_19_11} are active now)
(results {stata estimates replay col_4_23:col_4_23} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient
{res}{txt}
{com}. rename c2 stderr
{res}{txt}
{com}. 
. gen regression = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
variable {bf}regression{sf} was {bf}{res}str8{sf}{txt} now {bf}{res}str10{sf}
{txt}(1 real change made)
variable {bf}regression{sf} was {bf}{res}str10{sf}{txt} now {bf}{res}str11{sf}
{txt}(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient stderr , studylabel(regression)
{txt}(638 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}12
{col 8}{txt}Study label:  {res}regression
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient
{txt}{col 11}Std. Err.:  {res}stderr
{txt}{col 9}Study label:  {res}regression

{txt}Meta-analysis summary{col 43}Number of studies = {res}    12
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 1.3743
{txt}{col 53}I2 (%) = {res}  77.41
{txt}{col 57}H2 = {res}   4.43

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_89{col 19}{c |}{res}{space 6}   -2.483{col 35}{space 3}   -4.136{col 47}{space 3}   -0.831{col 59}{space 5}10.64
{col 1}{txt}         col_4_93{col 19}{c |}{res}{space 6}   -1.815{col 35}{space 3}   -4.235{col 47}{space 3}    0.605{col 59}{space 5} 7.65
{col 1}{txt}         col_4_96{col 19}{c |}{res}{space 6}    2.155{col 35}{space 3}   -0.494{col 47}{space 3}    4.804{col 59}{space 5} 6.93
{col 1}{txt}         col_4_00{col 19}{c |}{res}{space 6}    1.894{col 35}{space 3}   -0.005{col 47}{space 3}    3.794{col 59}{space 5} 9.59
{col 1}{txt}         col_4_04{col 19}{c |}{res}{space 6}   -0.459{col 35}{space 3}   -2.696{col 47}{space 3}    1.778{col 59}{space 5} 8.29
{col 1}{txt}         col_4_08{col 19}{c |}{res}{space 6}    1.896{col 35}{space 3}   -0.199{col 47}{space 3}    3.991{col 59}{space 5} 8.82
{col 1}{txt}         col_4_11{col 19}{c |}{res}{space 6}   -5.703{col 35}{space 3}  -13.227{col 47}{space 3}    1.821{col 59}{space 5} 1.38
{col 1}{txt}         col_4_15{col 19}{c |}{res}{space 6}  -17.917{col 35}{space 3}  -30.844{col 47}{space 3}   -4.989{col 59}{space 5} 0.49
{col 1}{txt}         col_4_16{col 19}{c |}{res}{space 6}    0.393{col 35}{space 3}    0.014{col 47}{space 3}    0.772{col 59}{space 5}15.71
{col 1}{txt}       col_4_19_4{col 19}{c |}{res}{space 6}   -0.404{col 35}{space 3}   -1.093{col 47}{space 3}    0.285{col 59}{space 5}14.81
{col 1}{txt}      col_4_19_11{col 19}{c |}{res}{space 6}   -0.042{col 35}{space 3}   -0.918{col 47}{space 3}    0.834{col 59}{space 5}14.09
{col 1}{txt}         col_4_23{col 19}{c |}{res}{space 6}    1.863{col 35}{space 3}   -5.075{col 47}{space 3}    8.801{col 59}{space 5} 1.60
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}   -0.084{col 35}{space 3}   -1.007{col 47}{space 3}    0.839
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}-0.18{txt}{col 50}Prob > |z| = {res}0.8579
{txt}Test of homogeneity: Q = chi2({res}11{txt}) = {res}34.98{txt}{col 52}Prob > Q = {res}0.0002
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient
{txt}{col 11}Std. Err.:  {res}stderr
{txt}{col 9}Study label:  {res}regression

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_our_weights.png", replace    
{txt}(file Results/Figures_Electoral/forestplot_our_weights.png written in PNG format)

{com}. 
. 
. * Replication period
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_89 col_4_93 col_4_96 col_4_00 col_4_04 col_4_08 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_ours_c]
{txt}  4{com}.     local se = _se[top_prizes_gdp_ours_c]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_89:col_4_89} are active now)
(results {stata estimates replay col_4_93:col_4_93} are active now)
(results {stata estimates replay col_4_96:col_4_96} are active now)
(results {stata estimates replay col_4_00:col_4_00} are active now)
(results {stata estimates replay col_4_04:col_4_04} are active now)
(results {stata estimates replay col_4_08:col_4_08} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient_pre
{res}{txt}
{com}. rename c2 stderr_pre
{res}{txt}
{com}. 
. gen regression_pre_w = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression_pre_w = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression_pre_w{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient_pre stderr_pre , studylabel(regression_pre_w)
{txt}(644 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}6
{col 8}{txt}Study label:  {res}regression_pre_w
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient_pre

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr_pre
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_pre
{txt}{col 11}Std. Err.:  {res}stderr_pre
{txt}{col 9}Study label:  {res}regression_pre_w

{txt}Meta-analysis summary{col 43}Number of studies = {res}     6
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 3.2398
{txt}{col 53}I2 (%) = {res}  73.77
{txt}{col 57}H2 = {res}   3.81

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_89{col 19}{c |}{res}{space 6}   -2.483{col 35}{space 3}   -4.136{col 47}{space 3}   -0.831{col 59}{space 5}18.78
{col 1}{txt}         col_4_93{col 19}{c |}{res}{space 6}   -1.815{col 35}{space 3}   -4.235{col 47}{space 3}    0.605{col 59}{space 5}15.57
{col 1}{txt}         col_4_96{col 19}{c |}{res}{space 6}    2.155{col 35}{space 3}   -0.494{col 47}{space 3}    4.804{col 59}{space 5}14.64
{col 1}{txt}         col_4_00{col 19}{c |}{res}{space 6}    1.894{col 35}{space 3}   -0.005{col 47}{space 3}    3.794{col 59}{space 5}17.75
{col 1}{txt}         col_4_04{col 19}{c |}{res}{space 6}   -0.459{col 35}{space 3}   -2.696{col 47}{space 3}    1.778{col 59}{space 5}16.33
{col 1}{txt}         col_4_08{col 19}{c |}{res}{space 6}    1.896{col 35}{space 3}   -0.199{col 47}{space 3}    3.991{col 59}{space 5}16.93
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}    0.149{col 35}{space 3}   -1.539{col 47}{space 3}    1.837
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}0.17{txt}{col 50}Prob > |z| = {res}0.8627
{txt}Test of homogeneity: Q = chi2({res}5{txt}) = {res}20.50{txt}{col 52}Prob > Q = {res}0.0010
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_pre
{txt}{col 11}Std. Err.:  {res}stderr_pre
{txt}{col 9}Study label:  {res}regression_pre_w

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_pre_weights.png", replace            
{txt}(file Results/Figures_Electoral/forestplot_pre_weights.png written in PNG format)

{com}. 
. 
. * Out-of-sample period
. matrix results = J(12, 2, .)
{txt}
{com}. local regression_names "col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23"
{txt}
{com}. 
. local i = 1
{txt}
{com}. foreach regname in col_4_11 col_4_15 col_4_16 col_4_19_4 col_4_19_11 col_4_23 {c -(}
{txt}  2{com}.     est restore `regname'
{txt}  3{com}.     local coef = _b[top_prizes_gdp_ours_c]
{txt}  4{com}.     local se = _se[top_prizes_gdp_ours_c]
{txt}  5{com}.     matrix results[`i', 1] = `coef'
{txt}  6{com}.     matrix results[`i', 2] = `se'
{txt}  7{com}.     local i = `i' + 1
{txt}  8{com}. {c )-}
{txt}(results {stata estimates replay col_4_11:col_4_11} are active now)
(results {stata estimates replay col_4_15:col_4_15} are active now)
(results {stata estimates replay col_4_16:col_4_16} are active now)
(results {stata estimates replay col_4_19_4:col_4_19_4} are active now)
(results {stata estimates replay col_4_19_11:col_4_19_11} are active now)
(results {stata estimates replay col_4_23:col_4_23} are active now)

{com}. 
. svmat double results, names(col)
{txt}
{com}. rename c1 coefficient_post
{res}{txt}
{com}. rename c2 stderr_post
{res}{txt}
{com}. 
. gen regression_post_w = ""
{txt}(650 missing values generated)

{com}. local i = 1
{txt}
{com}. foreach regname in `regression_names' {c -(}
{txt}  2{com}.     replace regression_post_w = "`regname'" in `i'
{txt}  3{com}.     local i = `i' + 1
{txt}  4{com}. {c )-}
{txt}variable {bf}regression_post_w{sf} was {bf}{res}str1{sf}{txt} now {bf}{res}str8{sf}
{txt}(1 real change made)
(1 real change made)
(1 real change made)
variable {bf}regression_post_w{sf} was {bf}{res}str8{sf}{txt} now {bf}{res}str10{sf}
{txt}(1 real change made)
variable {bf}regression_post_w{sf} was {bf}{res}str10{sf}{txt} now {bf}{res}str11{sf}
{txt}(1 real change made)
(1 real change made)

{com}. 
. meta set coefficient_post stderr_post , studylabel(regression_post_w)
{txt}(644 missing values generated)

Meta-analysis setting information

{col 2}Study information
{col 5}No. of studies:  {res}6
{col 8}{txt}Study label:  {res}regression_post_w
{col 9}{txt}Study size:  N/A

{col 8}Effect size
{col 15}Type:  Generic
{col 14}Label:  Effect Size
{col 11}Variable:  {res}coefficient_post

{col 10}{txt}Precision
{col 10}Std. Err.:  {res}stderr_post
{col 17}{txt}CI:  [{res}_meta_cil{txt}, {res}_meta_ciu{txt}]
{col 11}CI level:  {res}95{txt}%

{col 3}Model and method
{col 14}Model:  Random-effects
{col 13}Method:  REML

{com}. meta summ
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_post
{txt}{col 11}Std. Err.:  {res}stderr_post
{txt}{col 9}Study label:  {res}regression_post_w

{txt}Meta-analysis summary{col 43}Number of studies = {res}     6
{txt}Random-effects model{col 43}Heterogeneity:
Method: REML {res}{txt}{col 55}tau2 = {res} 0.1279
{txt}{col 53}I2 (%) = {res}  33.70
{txt}{col 57}H2 = {res}   1.51

{txt}{hline 18}{c TT}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            Study{col 19}{c |}    Effect Size{col 35}    [95% Conf. Interval]{col 59}  % Weight
{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}         col_4_11{col 19}{c |}{res}{space 6}   -5.703{col 35}{space 3}  -13.227{col 47}{space 3}    1.821{col 59}{space 5} 0.51
{col 1}{txt}         col_4_15{col 19}{c |}{res}{space 6}  -17.917{col 35}{space 3}  -30.844{col 47}{space 3}   -4.989{col 59}{space 5} 0.17
{col 1}{txt}         col_4_16{col 19}{c |}{res}{space 6}    0.393{col 35}{space 3}    0.014{col 47}{space 3}    0.772{col 59}{space 5}45.66
{col 1}{txt}       col_4_19_4{col 19}{c |}{res}{space 6}   -0.404{col 35}{space 3}   -1.093{col 47}{space 3}    0.285{col 59}{space 5}30.02
{col 1}{txt}      col_4_19_11{col 19}{c |}{res}{space 6}   -0.042{col 35}{space 3}   -0.918{col 47}{space 3}    0.834{col 59}{space 5}23.04
{col 1}{txt}         col_4_23{col 19}{c |}{res}{space 6}    1.863{col 35}{space 3}   -5.075{col 47}{space 3}    8.801{col 59}{space 5} 0.60
{txt}{hline 18}{c +}{hline 15}{hline 12}{hline 12}{hline 10}
{col 1}            theta{col 19}{c |}{res}{space 6}   -0.000{col 35}{space 3}   -0.539{col 47}{space 3}    0.538
{txt}{hline 18}{c BT}{hline 15}{hline 12}{hline 12}{hline 10}
Test of theta = 0: z = {res}-0.00{txt}{col 50}Prob > |z| = {res}0.9991
{txt}Test of homogeneity: Q = chi2({res}5{txt}) = {res}14.30{txt}{col 52}Prob > Q = {res}0.0138
{txt}
{com}. meta forestplot, xline(0)
{res}
{txt}{col 3}Effect-size label:  Effect Size
{col 9}Effect size:  {res}coefficient_post
{txt}{col 11}Std. Err.:  {res}stderr_post
{txt}{col 9}Study label:  {res}regression_post_w

{txt}
{com}. graph export "${c -(}figures{c )-}forestplot_post_weights.png", replace   
{txt}(file Results/Figures_Electoral/forestplot_post_weights.png written in PNG format)

{com}.                 
. restore
{txt}
{com}. 
. * Table A13: Estimated Effects of Lottery Winnings on Province-Level Vote Share for the Incumbent Party - Meta Analyses: created manually using results of meta analyses above
. 
. 
. 
. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}C:\Users\david\Dropbox\Spanish_Lottery\StataDos_RScripts\202406 Analysis\Ours_replication_pkg\NEW AND FINAL REPPKG\Logs\MainPaper_ElectoralEvidence_byelection_Tables.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}31 Oct 2025, 18:38:14
{txt}{.-}
{smcl}
{txt}{sf}{ul off}